sidartha wp 6 report 1 appendix detection methodology · sidarthasidartha european emergency...
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SIDARTHaSIDARTHaSIDARTHaSIDARTHa
European Emergency DataEuropean Emergency DataEuropean Emergency DataEuropean Emergency Data----based Syndromic Surveillance Systembased Syndromic Surveillance Systembased Syndromic Surveillance Systembased Syndromic Surveillance System
Grant Agreement No. 2007208Grant Agreement No. 2007208Grant Agreement No. 2007208Grant Agreement No. 2007208
AppendixAppendixAppendixAppendix
Developing Algorithms forDeveloping Algorithms forDeveloping Algorithms forDeveloping Algorithms for Early Public Health Threat Early Public Health Threat Early Public Health Threat Early Public Health Threat
DetDetDetDetectionectionectionection in Europein Europein Europein Europe ReReReResults from the SIDARTHa projectsults from the SIDARTHa projectsults from the SIDARTHa projectsults from the SIDARTHa project Draft report (January 2010)Draft report (January 2010)Draft report (January 2010)Draft report (January 2010)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 2
© SIDARTHa 2010 DRAFT January 2010
TablesTablesTablesTables
TTTTABLE ABLE ABLE ABLE 1111 QQQQUANTITY AND QUALITY UANTITY AND QUALITY UANTITY AND QUALITY UANTITY AND QUALITY ANALYSIS OF ANALYSIS OF ANALYSIS OF ANALYSIS OF EMD(AT)EMD(AT)EMD(AT)EMD(AT) AND OVERVIEW ON ADDEAND OVERVIEW ON ADDEAND OVERVIEW ON ADDEAND OVERVIEW ON ADDED OR RECODED VARIABLD OR RECODED VARIABLD OR RECODED VARIABLD OR RECODED VARIABLESESESES.... ........................................................................................................................................................................................................................................ 4444
TTTTABLE ABLE ABLE ABLE 2222 SSSSELECTION OF RELEVANTELECTION OF RELEVANTELECTION OF RELEVANTELECTION OF RELEVANT EVENTS IN EVENTS IN EVENTS IN EVENTS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) ........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 5555
TTTTABLE ABLE ABLE ABLE 3333 AAAA QQQQUANTITY AND QUALITY UANTITY AND QUALITY UANTITY AND QUALITY UANTITY AND QUALITY ANALYSIS OF ANALYSIS OF ANALYSIS OF ANALYSIS OF EMD(AT)EMD(AT)EMD(AT)EMD(AT) .................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................... 6666
TTTTABLE ABLE ABLE ABLE 3333 BBBB AAAADDED OR RECODED VARIDDED OR RECODED VARIDDED OR RECODED VARIDDED OR RECODED VARIABLES IN THE ABLES IN THE ABLES IN THE ABLES IN THE EMD(AT)EMD(AT)EMD(AT)EMD(AT) DATA SETDATA SETDATA SETDATA SET .................................................................................................................................................................................................................................................................................................................................................................................................................................................... 7777
TTTTABLE ABLE ABLE ABLE 4444 AAAA QQQQUANTITY AND QUALITY UANTITY AND QUALITY UANTITY AND QUALITY UANTITY AND QUALITY ANALYSIS OF ANALYSIS OF ANALYSIS OF ANALYSIS OF EP(DE)EP(DE)EP(DE)EP(DE) ............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 9999
TTTTABLE ABLE ABLE ABLE 4444 BBBB AAAADDED OR RECODED VARIDDED OR RECODED VARIDDED OR RECODED VARIDDED OR RECODED VARIABLES OF ABLES OF ABLES OF ABLES OF EP(DE)EP(DE)EP(DE)EP(DE)................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 10101010
TTTTABLE ABLE ABLE ABLE 5555 VVVVALUES OF ALUES OF ALUES OF ALUES OF EP(DE)EP(DE)EP(DE)EP(DE) SPECIFIC VARIABLES ASPECIFIC VARIABLES ASPECIFIC VARIABLES ASPECIFIC VARIABLES AND THEIR USE FOR SYNND THEIR USE FOR SYNND THEIR USE FOR SYNND THEIR USE FOR SYNDROME GENERATIONDROME GENERATIONDROME GENERATIONDROME GENERATION ........................................................................................................................................................................................................................................................................................................ 12121212
TTTTABLE ABLE ABLE ABLE 6666 SSSSIGNALS IGNALS IGNALS IGNALS C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 BETWEEN BETWEEN BETWEEN BETWEEN 2003200320032003 AND AND AND AND 2008200820082008 IN IN IN IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) ........................................................................................................................................................................................................................................................................................................................................................................................................................ 13131313
TTTTABLE ABLE ABLE ABLE 7777 SSSSIGNALS IGNALS IGNALS IGNALS C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 BETWEEN BETWEEN BETWEEN BETWEEN JJJJULY ULY ULY ULY 2005200520052005 AND AND AND AND 2008200820082008 ININININEP(DE)EP(DE)EP(DE)EP(DE) ........................................................................................................................................................................................................................................................................................................................................................................................................ 15151515
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 3
© SIDARTHa 2010 DRAFT January 2010
FiguresFiguresFiguresFigures
FFFFIGURE IGURE IGURE IGURE 1111 NNNNUMBER OF HOSPITAL ADUMBER OF HOSPITAL ADUMBER OF HOSPITAL ADUMBER OF HOSPITAL ADMISSIONS IN MISSIONS IN MISSIONS IN MISSIONS IN ED(AT)ED(AT)ED(AT)ED(AT) PER MONTH IN PER MONTH IN PER MONTH IN PER MONTH IN 2008200820082008 (1(1(1(1 ==== JJJJANUARYANUARYANUARYANUARY,,,, 12121212 ==== DDDDECEMBERECEMBERECEMBERECEMBER)))) .................................................................................................................................................................................................... 16161616
FFFFIGURE IGURE IGURE IGURE 2222 NNNNUMBER OF HOSPITAL ADUMBER OF HOSPITAL ADUMBER OF HOSPITAL ADUMBER OF HOSPITAL ADMISSIONS IN MISSIONS IN MISSIONS IN MISSIONS IN ED(AT)ED(AT)ED(AT)ED(AT) PER WEEK IN PER WEEK IN PER WEEK IN PER WEEK IN 2008200820082008 ........................................................................................................................................................................................................................................................................................................................................................................................................ 16161616
FFFFIGURE IGURE IGURE IGURE 3333 AAAAVERAGE OF NUMBER OF VERAGE OF NUMBER OF VERAGE OF NUMBER OF VERAGE OF NUMBER OF HOSPITAL ADMISSIONS HOSPITAL ADMISSIONS HOSPITAL ADMISSIONS HOSPITAL ADMISSIONS IN IN IN IN ED(AT)ED(AT)ED(AT)ED(AT) PER DAY OF THE WEEK PER DAY OF THE WEEK PER DAY OF THE WEEK PER DAY OF THE WEEK IN IN IN IN 2008200820082008 ........................................................................................................................................................................................................................................................................ 17171717
FFFFIGURE IGURE IGURE IGURE 4444 HHHHOSPITAL ADMISSIONS IOSPITAL ADMISSIONS IOSPITAL ADMISSIONS IOSPITAL ADMISSIONS IN N N N ED(AT)ED(AT)ED(AT)ED(AT) PER GENDER AND MONTHPER GENDER AND MONTHPER GENDER AND MONTHPER GENDER AND MONTH IN IN IN IN 2008200820082008 ........................................................................................................................................................................................................................................................................................................................................................................................ 17171717
FFFFIGURE IGURE IGURE IGURE 5555 MMMMEAN AGE OF ADMITTED EAN AGE OF ADMITTED EAN AGE OF ADMITTED EAN AGE OF ADMITTED PATIENTS IN PATIENTS IN PATIENTS IN PATIENTS IN ED(AT)ED(AT)ED(AT)ED(AT) PER WEEK IN PER WEEK IN PER WEEK IN PER WEEK IN 2008200820082008 ............................................................................................................................................................................................................................................................................................................................................................................................................ 18181818
FFFFIGURE IGURE IGURE IGURE 6666 AAAAMOUNT OF HOSPITAL ADMOUNT OF HOSPITAL ADMOUNT OF HOSPITAL ADMOUNT OF HOSPITAL ADMISSIONS IN MISSIONS IN MISSIONS IN MISSIONS IN ED(AT)ED(AT)ED(AT)ED(AT) PER WEEK AND AGE CATPER WEEK AND AGE CATPER WEEK AND AGE CATPER WEEK AND AGE CATEGORY IN EGORY IN EGORY IN EGORY IN 2008200820082008 ................................................................................................................................................................................................................................................................................................ 18181818
FFFFIGURE IGURE IGURE IGURE 7777 AAAA NNNNUMBER OF ALL DISPATCUMBER OF ALL DISPATCUMBER OF ALL DISPATCUMBER OF ALL DISPATCH EVENTS IN H EVENTS IN H EVENTS IN H EVENTS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) FROM FROM FROM FROM 2003200320032003 TO TO TO TO 2008200820082008 ............................................................................................................................................................................................................................................................................................................................................................................ 19191919
FFFFIGURE IGURE IGURE IGURE 7777 BBBB NNNNUMBER OF RELEVANT DIUMBER OF RELEVANT DIUMBER OF RELEVANT DIUMBER OF RELEVANT DISPATCH EVENTS IN SPATCH EVENTS IN SPATCH EVENTS IN SPATCH EVENTS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) FROM FROM FROM FROM 2003200320032003 TO TO TO TO 2008200820082008............................................................................................................................................................................................................................................................................................................................................ 19191919
FFFFIGURE IGURE IGURE IGURE 8888 AAAA NNNNUMBER OF ALL DISPATCUMBER OF ALL DISPATCUMBER OF ALL DISPATCUMBER OF ALL DISPATCH EVENTS IN H EVENTS IN H EVENTS IN H EVENTS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) FROM FROM FROM FROM 2003200320032003 TO TO TO TO 2008200820082008 PER MONTHPER MONTHPER MONTHPER MONTH ............................................................................................................................................................................................................................................................................................................ 20202020
FFFFIGURE IGURE IGURE IGURE 8888 BBBB NNNNUMBER OF RELEVANT DIUMBER OF RELEVANT DIUMBER OF RELEVANT DIUMBER OF RELEVANT DISPATCH EVENTS IN SPATCH EVENTS IN SPATCH EVENTS IN SPATCH EVENTS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) FROM FROM FROM FROM 2003200320032003 TO TO TO TO 2008200820082008 PER MONTHPER MONTHPER MONTHPER MONTH ........................................................................................................................................................................................................................................................................ 22220000
FFFFIGURE IGURE IGURE IGURE 9999 AAAA AAAAVERAGE NUMBER OF ALLVERAGE NUMBER OF ALLVERAGE NUMBER OF ALLVERAGE NUMBER OF ALL DAILY DISPATCH EVENTDAILY DISPATCH EVENTDAILY DISPATCH EVENTDAILY DISPATCH EVENTS IN S IN S IN S IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) FOR THE PERIOD FOR THE PERIOD FOR THE PERIOD FOR THE PERIOD 2003200320032003 TO TO TO TO 2008200820082008 .................................................................................................................................................................................................................................... 21212121
FFFFIGURE IGURE IGURE IGURE 9999 BBBB AAAAVERAGE NUMBER OF ALLVERAGE NUMBER OF ALLVERAGE NUMBER OF ALLVERAGE NUMBER OF ALL DAILY DISPATCH EVENTDAILY DISPATCH EVENTDAILY DISPATCH EVENTDAILY DISPATCH EVENTS IN S IN S IN S IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) FOR THE PERIOD FOR THE PERIOD FOR THE PERIOD FOR THE PERIOD 2003200320032003 TO TO TO TO 2008200820082008 .................................................................................................................................................................................................................................... 22221111
FFFFIGURE IGURE IGURE IGURE 10101010 NNNNUMBER OF UMBER OF UMBER OF UMBER OF EPEPEPEP CASES IN CASES IN CASES IN CASES IN EP(DE),EP(DE),EP(DE),EP(DE), 01/07200501/07200501/07200501/072005 TO TO TO TO 31/12/200831/12/200831/12/200831/12/2008 ............................................................................................................................................................................................................................................................................................................................................................................................ 22222222
FFFFIGURE IGURE IGURE IGURE 11111111 NNNNUMBER OF UMBER OF UMBER OF UMBER OF EPEPEPEP CASES IN CASES IN CASES IN CASES IN EP(DE)EP(DE)EP(DE)EP(DE) PER MONTHPER MONTHPER MONTHPER MONTH,,,, 01/07200501/07200501/07200501/072005 TO TO TO TO 31/12/200831/12/200831/12/200831/12/2008 (1=J(1=J(1=J(1=JANUARYANUARYANUARYANUARY,,,, 12=D12=D12=D12=DECEMBERECEMBERECEMBERECEMBER)))) ................................................................................................................................................ 22222222
FFFFIGURE IGURE IGURE IGURE 12121212 NNNNUMBER OF UMBER OF UMBER OF UMBER OF EPEPEPEP CASES IN CASES IN CASES IN CASES IN EP(DE)EP(DE)EP(DE)EP(DE) PER WEEKPER WEEKPER WEEKPER WEEK,,,, 01/07200501/07200501/07200501/072005 TO TO TO TO 31/12/200831/12/200831/12/200831/12/2008 .................................................................................................................................................................................................................................................................................................................................... 23232323
FFFFIGURE IGURE IGURE IGURE 13131313 NNNNUMBER OF MALE AND FEUMBER OF MALE AND FEUMBER OF MALE AND FEUMBER OF MALE AND FEMALE MALE MALE MALE EPEPEPEP CASES IN CASES IN CASES IN CASES IN EP(DE)EP(DE)EP(DE)EP(DE) 01/072001/072001/072001/072005050505 TO TO TO TO 31/12/200831/12/200831/12/200831/12/2008 ............................................................................................................................................................................................................................................................................................ 23232323
FFFFIGURE IGURE IGURE IGURE 14141414 MMMMEAN AGE OF EAN AGE OF EAN AGE OF EAN AGE OF EPEPEPEP CASES IN CASES IN CASES IN CASES IN EP(DE)EP(DE)EP(DE)EP(DE) PER WEEKPER WEEKPER WEEKPER WEEK,,,, 01/07200501/07200501/07200501/072005 TO TO TO TO 31/12/200831/12/200831/12/200831/12/2008 ............................................................................................................................................................................................................................................................................................................................ 24242424
FFFFIGURE IGURE IGURE IGURE 15151515 EPEPEPEP CASES IN CASES IN CASES IN CASES IN EP(DE)EP(DE)EP(DE)EP(DE) PER WEEK AND AGE CATPER WEEK AND AGE CATPER WEEK AND AGE CATPER WEEK AND AGE CATEGORY IN EGORY IN EGORY IN EGORY IN 2006,2006,2006,2006, 2007200720072007 AND AND AND AND 2008200820082008 ........................................................................................................................................................................................................................................................................................................................ 25252525
FFFFIGURE IGURE IGURE IGURE 16161616 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN ED(AT)ED(AT)ED(AT)ED(AT) ADMISSIONS IN ADMISSIONS IN ADMISSIONS IN ADMISSIONS IN 2008200820082008 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ............................................................................................................................................................................................................................................................................................................................ 26262626
FFFFIGURE IGURE IGURE IGURE 17171717 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) IN IN IN IN 2003200320032003 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ................................................................................................................................................................................................................................................................................................................................................................................ 27272727
FFFFIGURE IGURE IGURE IGURE 18181818 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) IN IN IN IN 2004200420042004 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ................................................................................................................................................................................................................................................................................................................................................................................ 27272727
FFFFIGURE IGURE IGURE IGURE 19191919 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) IN IN IN IN 2005200520052005 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ................................................................................................................................................................................................................................................................................................................................................................................ 28282828
FFFFIGURE IGURE IGURE IGURE 20202020 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN TTTTYROL DISPATCH DATA IYROL DISPATCH DATA IYROL DISPATCH DATA IYROL DISPATCH DATA IN N N N 2006200620062006 ((((UNSTRATIFIED BASELIUNSTRATIFIED BASELIUNSTRATIFIED BASELIUNSTRATIFIED BASELINENENENE)))) .................................................................................................................................................................................................................................................................................................................... 28282828
FFFFIGURE IGURE IGURE IGURE 21212121 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) IN IN IN IN 2007200720072007 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ................................................................................................................................................................................................................................................................................................................................................................................ 29292929
FFFFIGURE IGURE IGURE IGURE 22222222 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) IN IN IN IN 2222008008008008 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ................................................................................................................................................................................................................................................................................................................................................................................ 29292929
FFFFIGURE IGURE IGURE IGURE 23232323 OOOOCCURRENCE OF SIGNALSCCURRENCE OF SIGNALSCCURRENCE OF SIGNALSCCURRENCE OF SIGNALS OF THE OF THE OF THE OF THE C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 ALGORITHM IN ALGORITHM IN ALGORITHM IN ALGORITHM IN EMD(AT)EMD(AT)EMD(AT)EMD(AT) ((((RELEVANT CASESRELEVANT CASESRELEVANT CASESRELEVANT CASES)))) IN IN IN IN 2003200320032003 TO TO TO TO 2008200820082008 ................................................................................................................................................................ 32323232
FFFFIGURE IGURE IGURE IGURE 24242424 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN ED(DE)ED(DE)ED(DE)ED(DE) IN IN IN IN 2005200520052005 ((((FROM FROM FROM FROM JJJJULYULYULYULY)))) ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ................................................................................................................................................................................................................................................................................................................ 33333333
FFFFIGURE IGURE IGURE IGURE 25252525 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN ED(DE)ED(DE)ED(DE)ED(DE) IN IN IN IN 2006200620062006 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ............................................................................................................................................................................................................................................................................................................................................................................................ 33333333
FFFFIGURE IGURE IGURE IGURE 26262626 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS IN SIGNALS IN SIGNALS IN SIGNALS IN ED(DE)ED(DE)ED(DE)ED(DE) IN IN IN IN 2007200720072007 ((((UNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINUNSTRATIFIED BASELINEEEE)))) ............................................................................................................................................................................................................................................................................................................................................................................................ 34343434
FFFFIGURE IGURE IGURE IGURE 27272727 C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 SIGNALS ON SIGNALS ON SIGNALS ON SIGNALS ON GGGGOEPPINGEN DATA IN OEPPINGEN DATA IN OEPPINGEN DATA IN OEPPINGEN DATA IN 2008200820082008 ((((UNSTRATIFIED UNSTRATIFIED UNSTRATIFIED UNSTRATIFIED BASELINEBASELINEBASELINEBASELINE)))) .................................................................................................................................................................................................................................................................................................................................... 34343434
FFFFIGURE IGURE IGURE IGURE 28282828 OOOOCCURRENCE OF SIGNALSCCURRENCE OF SIGNALSCCURRENCE OF SIGNALSCCURRENCE OF SIGNALS OF THE OF THE OF THE OF THE C1,C1,C1,C1, C2,C2,C2,C2, C3C3C3C3 ALGORITHM IN ALGORITHM IN ALGORITHM IN ALGORITHM IN ED(DE)ED(DE)ED(DE)ED(DE) IN IN IN IN 2005200520052005----2008200820082008 ............................................................................................................................................................................................................................................................................................ 36363636
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 4
© SIDARTHa 2010 DRAFT January 2010
Name of variable Description of variable Scales of measurement Valid
fields
Missing fields Total
lines
ID ID of case Interval 30669 0 30669
Date Date of event Date, scale 30669 0 30669
Time Time (24hrs decimals) Text (Categorical), nominal 30669 0 30669
Sex Sex of patient Text (Categorical), nominal 30669 0 30669
Age Age of patient Interval 30669 0 30669
Residence Residence of patient (in ZIPcode, city and country) Free text 30669 0 30669
Added or recoded variables
Month Month of event Interval 30669 0 30669
Weeks Week of the year Interval 30669 0 30669
Wday Day of the week (Monday, Tuesday, …) Ordinal 30669 0 30669
Sex Sex of patient Nominal 30669 0 30669
ZIPcodes ZIPcode of patient Ordinal 30669 0 30669
ZIPcategory Region of patient (categorised by ZIPcode) Ordinal 30669 0 30669
Abstracted from files: EARS_TYROLhospital.xls and TYROL_hospital_18112009.sav
Table Table Table Table 1111 Quantity and quality analysis of EMD(AT) and overview on added or recoded variables. Quantity and quality analysis of EMD(AT) and overview on added or recoded variables. Quantity and quality analysis of EMD(AT) and overview on added or recoded variables. Quantity and quality analysis of EMD(AT) and overview on added or recoded variables.
Grey rows indicate the currently used variables
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 5
© SIDARTHa 2010 DRAFT January 2010
uebergeord_
Einsatzstichw
ort
Meaning/
Inclusion Y/N
Rule AMPDS_
HBS
AMPDS_D
ispositions
stufe
AMPDS_S
ubcode
Einsatzcode (total code made up from the other variables)
ALP- alpine/Y EXCEPT 45
46
47
48
99
codes techncal description of rescue actions in mountains
codes for example number of persons buried by an avalanche
codes accidents with aircrafts
codes accidents of lifts
codes service activities
AMB- EMS stand-by for events like concerts and festivals/N
ANM- Non-tyrolean EMS brings pt to Tyrolean hospital/N
BEI- EMS stand-by for other incidents, not in use/N
BR- Bergrettung/Mountain Rescue Service/N
DF- Dienstfahrt (service drive)/N
FW- fire department/Y (see restrictions) ONLY 52
66
66
O
C
C
2
1
2
FW-52O2 (Gefahrenmeldenalage, medical alert)
FW-66C1 (Odor strange/unknown, inside, with patients)
FW-66C2 (Odor strange/unknown, outside, with patients)
FZG- technical coding, not in use/N
HNR- in-house emergency call/Y all all all all all
KT- transportation/Y (see restrictions) ONLY 90
91
KT-91… (ambulance)
LS- technical coding, not in use/N
NEF- technical coding, not in use/N
OST- technical coding, not in use/N
PR- technical coding, not in use/N
RD- Emergency Medical Service/Y EXCEPT 45
46
47
48
99
codes techncal description of rescue actions in mountains
codes for example number of persons buried by an avalanche
codes accidents with aircrafts
codes accidents of lifts
codes service activities
SON- Test alarm/N
V- transportation passed on to other EMS/N
Purpose of historical
data analysis
Variables
Unspecific syndrome
(general emergency
medical demand)
Table Table Table Table 2222 Selection of relevant events in EMD(AT)Selection of relevant events in EMD(AT)Selection of relevant events in EMD(AT)Selection of relevant events in EMD(AT)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 6
© SIDARTHa 2010 DRAFT January 2010
Name of variable Description of variable Scales of measurement Valid
fields
Missing
fields
Illogical
fields
Total
lines
ID ID of case Interval 937604 0 0 937604
Datum_ZP_alarm Date Date 937604 0 0 937604
MAIN-event nr Main event number Interval 937604 0 0 937604
Event nr event number Interval 937604 0 0 937604
Ressourcentyp Which ressource/vehicle was sent Text (Categorical) 937604 0 0 937604
Funkruf Individual Name of Vehicle (radio call name) Text (Categorical) 937604 0 0 937604
Ressourcentyp_Verwendung Which ressource/vehicle was sent (same as Ressourcentyp) Text (Categorical) 937579 25 0 937604
Wache Post where the Vehicle is stationed Text (Categorical) 929833 7760 11 937604
übergeord_Einsatzstichwort Part of "Einsatzcode" (Event type) Text (Categorical) 937525 79 0 937604
Einsatzcode Event Code (complete AMPDS Code) Text (Categorical) 937537 66 1 937604
AMPDS_Code Part of "Einsatzcode" Text (Categorical) 933546 2414 1644 937604
AMPDS_HBS Part of "Einsatzcode" (Main Complaint) Text (Categorical) 933540 2414 1650 937604
AMPDS_Dispositionsstufe Part of "Einsatzcode" (Severity) Text (Categorical) 935157 2436 11* 937604
AMPDS_Subcode Part of "Einsatzcode" Text (Categorical) 934065 3520 19* 937604
ZP_Alarm Date and time of alarm Date and Time 937604 0 0 937604
EO_Staat Country Text (Categorical) 937492 112 0 937604
EO_Bundesland Region/State Free text 935628 1976 0 937604
EO_PLZ ZIP code Ordinal 733443 203720 441 937604
EO_Ort City Free text 935648 1956 0 937604
EO_Straße1 Street Free text 920594 16732 278 937604
EO_HNr House number Interval 858621 78977 6 937604
EO_Adressobjekt Object of identification on location Free text 623757 52970 260877 937604
EO_Xkoordinate X coordinates Interval 937604 0 0 937604
EO_Ykoordinate Y coordinates Interval 937604 0 0 937604
NACA NACA Score = severity Ordinal 66148 871455 1 937604
Abstracted from files: Tyrol_Dispatch_data.xls and Tyrol Dispatch 1-12-2009.sav
Table Table Table Table 3333 A Quantity and quality analysis of EMD(AT)A Quantity and quality analysis of EMD(AT)A Quantity and quality analysis of EMD(AT)A Quantity and quality analysis of EMD(AT)
Grey rows indicate the currently used variables
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 7
© SIDARTHa 2010 DRAFT January 2010
Name of
added/recoded
variable
Description of variable Scales of
measurement
Valid fields Missing fields Illogical fields Total lines
Wday Day of the week (Monday, Tuesday, …) Ordinal 937604 0 0 937604
Yweek Week of the year Numeric 937604 0 0 937604
Ymonth Month of the year Interval 937604 0 0 937604
Filter Filter variable to extract relevant events out of the data set (based on the selection criteria
described in table 2)
Nominal
Table 3 B Added or recoded variables in the EMD(AT) data setTable 3 B Added or recoded variables in the EMD(AT) data setTable 3 B Added or recoded variables in the EMD(AT) data setTable 3 B Added or recoded variables in the EMD(AT) data set
Grey rows indicate the currently used variables
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 8
© SIDARTHa 2010 DRAFT January 2010
Name of variable Description of variable Scales of
measurement
Valid
fields
Missing fields Illogical fields Total lines
ID ID of case Interval 14869 0 0 14869
VERSION Version of information technology used Interval 14869 0 0 14869
GKZ community code of the event Ordinal 14797 0 72 14869
PLZ zip code of the event Ordinal 5 0 14864 14869
EINSAORT place of the event, e.g., home, work place Nominal 14543 0 326 14869
RD_EINS kind of response = severity code (highest priority, non highest priority response) Nominal 14869 0 0 14869
RETTMITT kind of response resource/vehicle = severity code (highest priority, non highest priority
response)
Nominal 4068 0 10801 14869
DATUM date Date 14869 0 0 14869
Tag Day Interval 14869 0 0 14869
Monat Month Interval 14869 0 0 14869
Jahr Year Interval 14869 0 0 14869
ZALARM Time of alarm (alarming the ambulance) Time 12674 0 2195 14869
ZABFST Time of sending an ambulance (start driving) Time 12689 0 2180 14869
ZANKE_NA Time of arrival at scene (ambulance crew) time 3 14866 0 14869
ZANKE_RD Time of arrival at scene (emergency physician) Time 12696 0 2173 14869
ZTRAB Time of leaving with patient Time 10100 0 4769 14869
ZUEBG Time of transferral to hospital Time 12744 0 2125 14869
RLSTINDK dispatch code Nominal 2172 0 12697 14869
GEBDAT date of birth patient Date 13922 0 947 14869
PATALTER age patient year/month 13916 0 953 14869
GESCHL sex patient Nominal 14087 0 782 14869
GCS1 Glasgow Coma Scale = severity code Nominal 14032 0 837 14869
AF1 First Respiratory Status Interval 12004 0 2865
14869
SAOZ1 First status pulse oximetry, oxygen saturation Interval 11734 0 3135
14869
SCHMERZ1 Pain Interval 12870 0 1999
14869
MEES1 Mainz Emergency Evaluation Score 1 = severity code Nominal 3691 0 11178
14869
ATM1 First Breathing status Nominal 13024 0 1845 14869
KRANK1 Cerebrovascular diseases Nominal 982 0 13887 14869
KRANK2 Cardiovascular diseases Nominal 1994 0 12875 14869
KRANK3 Breathing Problems (ILI and respiratory diseases) Nominal 639 0 14230 14869
KRANK4 Abdominal Pain (Gastrointestinal) Nominal 576 0 14293 14869
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 9
© SIDARTHa 2010 DRAFT January 2010
Name of variable Description of variable Scales of
measurement
Valid
fields
Missing fields Illogical fields Total lines
KRANK5 Psychiatric diseases Nominal 228 0 14641 14869
KRANK6 Metabolic diseases Nominal 530 0 14339 14869
KRANK7 gynecologic events Nominal 107 0 14762 14869
KRANK8 other diseases Nominal 164 0 14705 14869
ICD1 International Classification of Disease codes main diagnosis (ICD 10) Nominal 10431 4438 0 14869
ICD2 International Classification of Disease codes 1st secondary diagnosis (ICD 10) Nominal 4273 10596 0 14869
ICD3 International Classification of Disease codes 2nd secondary diagnosis (ICD 10) Nominal 1200 13669 0 14869
ZIELKLDI main diagnosis hospital (ICD10 code) Nominal 0 14869 0 14869
NACA NACA Score = severity code Nominal 13400 0 1469 14869
KTEMP First status: body core temperature Interval 0 0 14869
14869
GCS2 Glasgow Coma Scale = severity code (transferral) Nominal 13303 0 1566 14869
MEES2 Mainz Emergency Evaluation Score 2 = severity code (transferral) Nominal 3676 0 11193
14869
Abstracted from files: EARS_on_goppingen1.xls and Goppingen Data.sav
Table Table Table Table 4444 A Quantity and quality analysis of EP(DE)A Quantity and quality analysis of EP(DE)A Quantity and quality analysis of EP(DE)A Quantity and quality analysis of EP(DE)
Grey rows indicate the currently used variables
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 10
© SIDARTHa 2010 DRAFT January 2010
Name of
added/recoded
variable
Description of variable Scales of
measurement
Valid fields Missing fields Illogical fields Total lines
Age Age in years calculated from the difference between DATUM and GEBDAT Interval 13922 947 0 14869
Sex Sex Nominal 14087 782 0 14869
Wday Day of the week (Monday, Tuesday, …) Ordinal 14869 0 0 14869
Yweek Week of the year Numeric 14869 0 0 14869
ATM_1 First Breathing status Nominal 13034 1835 0 14869
KRANK_1 Cerebrovascular diseases Nominal 14869 0 0 14869
KRANK_2 Cardiovascular diseases Nominal 14869 0 0 14869
KRANK_3 Breathing Problems (ILI and respiratory diseases) Nominal 14869 0 0 14869
KRANK_4 Abdominal Pain (Gastrointestinal) Nominal 14869 0 0 14869
KRANK_5 Psychiatric diseases Nominal 14869 0 0 14869
KRANK_6 Metabolic diseases Nominal 14869 0 0 14869
KRANK_7 gynecologic events Nominal 14869 0 0 14869
KRANK_8 other diseases Nominal 14869 0 0 14869
Table 4 B Added or recoded variableTable 4 B Added or recoded variableTable 4 B Added or recoded variableTable 4 B Added or recoded variables of EP(DE)s of EP(DE)s of EP(DE)s of EP(DE)
Grey rows indicate the currently used variables
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 11
© SIDARTHa 2010 DRAFT January 2010
Variable Description
First status 1 2 3 4 5 6 7 8 9 10 11 12 13
ATM1 Breathing normal dyspnoea cyanosis spastic rales stridor Airway
obstruction
gasping apnoea mechanical
ventilation
EKG1 ECG findings sinus rhythm absolute
arrhythmia
AV block II AB-block
III
narrow QRS
tachycardia
wide QRS
tachycardia
VES monotop VES
polytop
ventricular
fibrillation
pulseless
electrical
activity
Asystole pace-
maker
rhythm
infarct
ECG
value - intervall
scale
GCS1 Glasgow Coma Scale 3 to 15
RRSYS1 systolic blood
pressure
0 to 300 mm Hg
HF1 heart rate 0 to 300 bpm
AF1 respiratory rate 0 to 50 breath
per minute
SAOZ1 pulse oximetry
oxygen saturation
0 to 100 %
SCHMERZ1 VAS pain score 0 to 10 points
KTEMP body core
temperature
0 to 45 ° Celsius
Variable Description
First status ILI R G T E
ATM1 Breathing 2 or 3 or 4
or 5
2 or 3 or 4 or
5
EKG1 ECG findings
GCS1 Glasgow Coma Scale
RRSYS1 systolic blood
pressure
HF1 heart rate
AF1 respiratory rate > 20 breath per
min
SAOZ1 pulse oximetry
oxygen saturation
SpO2 < 95% SpO2 < 95%
SCHMERZ1 VAS pain score VAS > 3
KTEMP body core
temperature
> 38.5 ° C
values
Syndromes
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 12
© SIDARTHa 2010 DRAFT January 2010
Variables Description
First status 1 2 3 4 5 6 7 8 9 10 11
KRANK1 CNS Disorders TIA / stroke intracranial
bleeding
seizure other CNS
disorder
KRANK2 heart / circulation
disorders
angina pectoris myocardial
infarction
Arrhythmia pulmonary
embolism
Pulmonary
oedema
hypertensive
emergency
orthostasis Syncope cardio-
vascular
arrest
other
cardio-
vascular
disease
PM / ICD
malfunction
KRANK3 airway disorders Asthma COPD
exacerbations
Aspiration Pneumonia /
bronchitis
Hyper-
ventilation
tetany
Croup /
Epiglottises
other
respiratory
disease
KRANK4 abdominal disorders acute abdomen Gastro-
intestinal
Bleeding
Colic other disease
abdomen
KRANK5 psychiatric disorders psychosis /
depression /
mania
increased
emotion
alcohol
intoxication
drug
intoxication
intoxication
medical drugs
withdrawal
alcohol / drugs /
medicine
Suicide
attempt
other
psychiatric
disorder
KRANK6 metabolic disease Hypo- hyper-
glycaemia
Dehydrated other
metabolic
disorder
KRANK7 gynaecological obstetric
emergency
childbirth vaginal bleeding other illness
Gynaecology
KRANK8 other diseases anaphylactic
reaction
hypothermia Drowning SIDS Other
intoxication
Final stage of
malignancy
Variable Description
ILI R G T E
KRANK1 CNS Disorders 3 or 4
KRANK2 heart / circulation
disorders
KRANK3 airway disorders 4 or 7 1 to 7
KRANK4 abdominal disorders 1 or 2 or 3 or 4
KRANK5 psychiatric disorders 3 or 4 or 5
KRANK6 metabolic disease 2
KRANK7 gynaecological obstetric
emergency
KRANK8 other diseases 5
values
Syndromes
Table Table Table Table 5555: : : : Values of EP(DE) specific variables and their use for syndrome generationValues of EP(DE) specific variables and their use for syndrome generationValues of EP(DE) specific variables and their use for syndrome generationValues of EP(DE) specific variables and their use for syndrome generation
ILI= Influenza-Like-Illness, R =Respiratory Syndrome, G=Gastrointestinal Syndrome, T=Intoxication Syndrome, E=Environment-related illness
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 13
© SIDARTHa 2010 DRAFT January 2010
SignalsSignalsSignalsSignals
C1C1C1C1 C2C2C2C2 C3C3C3C3
2003200320032003 - 5-8-2003 (Tu) 5-8-2003 (Tu) 6-8-2003 (We) 7-8-2003 (Th)
2004200420042004 3-2-2004 (Tu) 5-2-2004 (Th)
5-2-2004 (Th) 6-2-2004 (Fr) 7-2-2004 (Sa)
2005200520052005 - 23-6-2005 (Th) 23-6-2005 (Th) 24-6-2005 (Fr) 25-6-2005 (Sa)
2006200620062006 15-12-2006 (Fr) 27-12-2006 (We)
28-7-2006 (Fr) 27-12-2006 (We)
28-7-2006 (Fr) 29-7-2006 (Sa) 30-7-2006 (Su) 27-12-2006 (We) 28-12-2006 (Th) 29-12-2006 (Fr)
2007200720072007 14-5-2007 (Mo) 27-12-2007 (Th)
16-7-2007 (We) 17-7-2007 (Th) 27-12-2007 (Th) 28-12-2007 (Fr) 29-12-2007 (Sa)
16-7-2007 (We) 17-7-2007 (Th) 18-7-2007 (Fr) 19-7-2007 (Sa) 27-12-2007 (Th) 28-12-2007 (Fr) 29-12-2007 (Sa) 30-12-2007 (Su) 31-12-2007 (Mo)
2008200820082008 10-3-2008 (Mo) 29-12-2008 (Mo)
29-12-2008 (Mo)
29-12-2008 (Mo) 30-12-2008 (Tu) 31-12-2008 (We)
Table Table Table Table 6666 Signals C1, C2, C3 between 2003 and 2008 in EMD(AT)Signals C1, C2, C3 between 2003 and 2008 in EMD(AT)Signals C1, C2, C3 between 2003 and 2008 in EMD(AT)Signals C1, C2, C3 between 2003 and 2008 in EMD(AT)
(Mo=Monday, Tu=Tuesday, We=Wednesday, Th=Thursday, Fr=Friday, Sa=Saturday, Su=Sunday)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 14
© SIDARTHa 2010 DRAFT January 2010
SignalsSignalsSignalsSignals
C1C1C1C1 C2C2C2C2 C3C3C3C3
2020202005050505 16-7-2005 (Sa) 11-9-2005 (Su) 21-9-2005 (We) 4-10-2005 (Tu)
16-7-2005 (Sa) 21-9-2005 (We) 4-10-2005 (Tu)
16-7-2005 (Sa) 17-7-2005 (Su) 21-9-2005 (We) 22-9-2005 (Th) 23-9-2005 (Fr) 4-10-2005 (Tu) 5-10-2005 (We) 6-10-2005 (We)
2006200620062006 1-1-2006 (Su) 24-1-2006 (Tu) 2-3-2006 (Th) 17-4-2006 (Mo) 11-5-2006 (Th) 9-7-2006 (Su) 2-8-2006 (We) 17-8-2006 (Th) 29-9-2006 (Fr) 18-10-2006 (We) 30-11-2006 (Th) 8-12-2006 (Fr)
1-1-2006 (Su) 24-1-2006 (Tu) 2-3-2006 (Th) 4-3-2006 (Sa) 17-4-2006 (Mo) 2-8-2006 (We) 17-8-2006 (Th) 29-9-2006 (Fr) 30-11-2006 (Th)
1-1-2006 (Su) 2-1-2006 (Mo) 3-1-2006 (Tu) 24-1-2006 (Tu) 25-1-2006 (We) 26-1-2006 (Th) 2-3-2006 (Th) 3-3-2006 (Fr) 4-3-2006 (Sa) 5-3-2006 (Su) 6-3-2006 (Mo) 17-4-2006 (Mo) 18-4-2006 (Tu) 19-4-2006 (We) 2-8-2006 (We) 3-8-2006 (Th) 4-8-2006 (Fr) 17-8-2006 (Th) 18-8-2006 (Fr) 19-8-2006 (Sa) 29-9-2006 (Fr) 30-9-2006 (Sa) 1-10-2006 (Su) 30-11-2006 (Th) 1-12-2006 (Fr) 2-12-2006 (Sa)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 15
© SIDARTHa 2010 DRAFT January 2010
SignalsSignalsSignalsSignals
C1C1C1C1 C2C2C2C2 C3C3C3C3
2007 2007 2007 2007 1-1-2007 (Mo) 2-2-2007 (Fr) 13-3-2007 (Tu) 20-4-2007 (Fr) 31-8-2007 (Fr) 28-9-2007 (Fr) 10-10-2007 (We) 22-11-2007 (Th) 20-12-2007 (Th)
1-1-2007 (Mo) 27-3-2007 (Tu) 20-4-2007 (Fr) 21-4-2007 (Sa) 22-4-2007 (Su) 6-6-2007 (We) 16-6-2007 (Sa) 28-9-2007 (Fr) 11-10-2007 (Th) 23-11-2007 (Fr)
1-1-2007 (Mo) 2-1-2007 (Tu) 3-1-2007 (We) 27-3-2007 (Tu) 28-3-2007 (We) 29-3-2007 (Th) 20-4-2007 (Fr) 21-4-2007 (Sa) 22-4-2007 (Su) 23-4-2007 (Mo) 24-4-2007 (Tu) 6-6-2007 (We) 7-6-2007 (Th) 8-6-2007 (Fr) 16-6-2007 (Sa) 17-6-2007 (Su) 18-6-2007 (Mo) 28-9-2007 (Fr) 29-9-2007 (Sa) 30-9-2007 (Su) 11-10-2007 (Th) 12-10-2007 (Fr) 13-10-2007 (Fr) 23-11-2007 (Fr) 24-11-2007 (Sa) 25-11-2007 (Su)
2008200820082008 1-1-2008 (Tu) 24-5-2008 (Sa) 23-8-2008 (Sa) 21-9-2008 (Su) 3-11-2008 (Mo) 18-11-2008 (Tu) 12-12-2008 (Fr)
1-1-2008 (Tu) 28-3-2008 (Fr) 29-3-2008 (Sa) 24-5-2008 (Sa) 23-8-2008 (Sa) 25-8-2008 (Mo) 21-9-2008 (Su) 18-11-2008 (Tu)
1-1-2008 (Tu) 2-1-2008 (We) 3-1-2008 (Th) 28-3-2008 (Fr) 29-3-2008 (Sa) 30-3-2008 (Su) 31-3-2008 (Mo) 24-5-2008 (Sa) 25-5-2008 (Su) 26-5-2008 (Su) 23-8-2008 (Sa) 24-8-2008 (Su) 25-8-2008 (Mo) 26-8-2008 (Tu) 27-8-2008 (We) 21-9-2008 (Su) 22-9-2008 (Mo) 23-9-2008 (Tu) 18-11-2008 (Tu) 19-11-2008 (We) 20-11-2008 (Th)
Table Table Table Table 7777 Signals C1, C2, C3 between July 2005 and 2008 inSignals C1, C2, C3 between July 2005 and 2008 inSignals C1, C2, C3 between July 2005 and 2008 inSignals C1, C2, C3 between July 2005 and 2008 in EP(DE)EP(DE)EP(DE)EP(DE)
(Mo=Monday, Tu=Tuesday, We=Wednesday, Th=Thursday, Fr=Friday, Sa=Saturday, Su=Sunday)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 16
© SIDARTHa 2010 DRAFT January 2010
Descriptive analysis Descriptive analysis Descriptive analysis Descriptive analysis ED(AT)ED(AT)ED(AT)ED(AT)
Number of hospital admissions per month
2100
2200
2300
2400
2500
2600
2700
2800
2900
1 2 3 4 5 6 7 8 9 10 11 12
Figure Figure Figure Figure 1111 Number of hoNumber of hoNumber of hoNumber of hospital admissions in spital admissions in spital admissions in spital admissions in ED(AT)ED(AT)ED(AT)ED(AT) per month in 2008 (1 = January, 12 = December)per month in 2008 (1 = January, 12 = December)per month in 2008 (1 = January, 12 = December)per month in 2008 (1 = January, 12 = December)
(red line shows the average monthly admission, x =2,556)
Number of hospital admissions per week
0
100
200
300
400
500
600
700
800
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52
Figure Figure Figure Figure 2222 Number of hospital admissions in Number of hospital admissions in Number of hospital admissions in Number of hospital admissions in ED(AT) ED(AT) ED(AT) ED(AT) per week in 2008per week in 2008per week in 2008per week in 2008
(red line shows the average weekly admission, x =579)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 17
© SIDARTHa 2010 DRAFT January 2010
Average number of hospital admissions per day of the week
0
20
40
60
80
100
120
Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Figure Figure Figure Figure 3333 Average of number of hospital admissions in Average of number of hospital admissions in Average of number of hospital admissions in Average of number of hospital admissions in ED(AT) ED(AT) ED(AT) ED(AT) per day of the week in 2008per day of the week in 2008per day of the week in 2008per day of the week in 2008
Hospital admissions per month
0
200
400
600
800
1.000
1.200
1.400
1.600
Janu
ary
Febru
ary
Mar
chApr
il
May
June
July
Aug
ust
Sep
tem
ber
Octobe
r
Nove
mbe
r
Decem
ber
male
female
Figure Figure Figure Figure 4444 Hospital admissions in Hospital admissions in Hospital admissions in Hospital admissions in ED(AT) ED(AT) ED(AT) ED(AT) per geper geper geper gender and month in 2008nder and month in 2008nder and month in 2008nder and month in 2008
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 18
© SIDARTHa 2010 DRAFT January 2010
Mean age per week - Hospital admissions - 2008
42
44
46
48
50
52
54
56
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52
weeks
ag
e
Figure Figure Figure Figure 5555 Mean age of admitted patients in Mean age of admitted patients in Mean age of admitted patients in Mean age of admitted patients in ED(AT)ED(AT)ED(AT)ED(AT) per week in 2008per week in 2008per week in 2008per week in 2008
(red line shows the average weekly admission, x =52.3)
Admitted patients per age group
0
50
100
150
200
250
300
350
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52
weeks
0-25
26-64
=65
Figure Figure Figure Figure 6666 Amount of hospital admissAmount of hospital admissAmount of hospital admissAmount of hospital admissions in ions in ions in ions in ED(AT)ED(AT)ED(AT)ED(AT) per week and age category in 2008per week and age category in 2008per week and age category in 2008per week and age category in 2008
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 19
© SIDARTHa 2010 DRAFT January 2010
Descriptive analysis Descriptive analysis Descriptive analysis Descriptive analysis EMD(AT)EMD(AT)EMD(AT)EMD(AT)
Number of all dispatch actions per yeary = 6217,7x + 134506
R2 = 0,9493
0
20.000
40.000
60.000
80.000
100.000
120.000
140.000
160.000
180.000
200.000
2003 2004 2005 2006 2007 2008
Number of relevant dispatch actions per yeary = 4362,5x + 68227
R2 = 0,9389
0
20.000
40.000
60.000
80.000
100.000
120.000
140.000
160.000
180.000
200.000
2003 2004 2005 2006 2007 2008
Figure Figure Figure Figure 7777 A A A A ---- Number of all dispatch events in Number of all dispatch events in Number of all dispatch events in Number of all dispatch events in EMD(AT)EMD(AT)EMD(AT)EMD(AT) from 2003 to 2008from 2003 to 2008from 2003 to 2008from 2003 to 2008
B B B B –––– Number of relevant dispatch events in Number of relevant dispatch events in Number of relevant dispatch events in Number of relevant dispatch events in EMD(AT)EMD(AT)EMD(AT)EMD(AT) from 2003 to 2008from 2003 to 2008from 2003 to 2008from 2003 to 2008
A
B
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 20
© SIDARTHa 2010 DRAFT January 2010
Number of all dispatch actions per month
0
2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
18.000
1 2 3 4 5 6 7 8 9 10 11 12
2003
2004
2005
2006
2007
2008
Number of relevant dispatch actions per month
0
2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
18.000
1 2 3 4 5 6 7 8 9 10 11 12
Figure Figure Figure Figure 8888 A A A A ---- Number of all dispatch events in Number of all dispatch events in Number of all dispatch events in Number of all dispatch events in EMD(AT)EMD(AT)EMD(AT)EMD(AT) from 2003 to 2008 per month from 2003 to 2008 per month from 2003 to 2008 per month from 2003 to 2008 per month
B B B B ---- Number of relevant dispatch events in Number of relevant dispatch events in Number of relevant dispatch events in Number of relevant dispatch events in EMD(AT)EMD(AT)EMD(AT)EMD(AT) from 2003 to 2008 per month from 2003 to 2008 per month from 2003 to 2008 per month from 2003 to 2008 per month
(1=January, 12=December)
A
B
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 21
© SIDARTHa 2010 DRAFT January 2010
Average number of all dispatch actions
0
100
200
300
400
500
600
Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Average amount of relevant dispatch actions
0
100
200
300
400
500
600
Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Figure Figure Figure Figure 9999 A A A A ---- Average number of all daily dispatch events in Average number of all daily dispatch events in Average number of all daily dispatch events in Average number of all daily dispatch events in EMD(AT) EMD(AT) EMD(AT) EMD(AT) for the period 2003 to 2008for the period 2003 to 2008for the period 2003 to 2008for the period 2003 to 2008
B B B B ---- Average number of all daily dispatch events in Average number of all daily dispatch events in Average number of all daily dispatch events in Average number of all daily dispatch events in EMD(AT)EMD(AT)EMD(AT)EMD(AT) for the period 2003 to 2008for the period 2003 to 2008for the period 2003 to 2008for the period 2003 to 2008
A
B
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 22
© SIDARTHa 2010 DRAFT January 2010
Descriptive analysis Descriptive analysis Descriptive analysis Descriptive analysis EP(DE)EP(DE)EP(DE)EP(DE)
Number of cases per year
0
500
1.000
1.500
2.000
2.500
3.000
3.500
4.000
4.500
5.000
2005 2006 2007 2008
Figure Figure Figure Figure 10101010 NumNumNumNumber of EP ber of EP ber of EP ber of EP cases in cases in cases in cases in EP(DE)EP(DE)EP(DE)EP(DE), 01/072005 to 31/12/2008 , 01/072005 to 31/12/2008 , 01/072005 to 31/12/2008 , 01/072005 to 31/12/2008
N umber of EMS cases per mon th
0
50
100
150
200
250
300
350
400
450
500
1 2 3 4 5 6 7 8 9 10 11 12
2005
2006
2007
2008
Figure Figure Figure Figure 11111111 Number of EPNumber of EPNumber of EPNumber of EP cases in cases in cases in cases in EP(DE)EP(DE)EP(DE)EP(DE) per month, 01/072005 to 31/12/2008 (1=January, 12=December)per month, 01/072005 to 31/12/2008 (1=January, 12=December)per month, 01/072005 to 31/12/2008 (1=January, 12=December)per month, 01/072005 to 31/12/2008 (1=January, 12=December)
(red line shows the average number of cases for the whole period, x =354)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 23
© SIDARTHa 2010 DRAFT January 2010
Number of EMS cases per week
0
20
40
60
80
100
120
140
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
2005
2006
2007
2008
Figure Figure Figure Figure 12121212 Number of EPNumber of EPNumber of EPNumber of EP cases in cases in cases in cases in EP(DE) EP(DE) EP(DE) EP(DE) per week, 01/072005 to 31/12/2008 per week, 01/072005 to 31/12/2008 per week, 01/072005 to 31/12/2008 per week, 01/072005 to 31/12/2008
(red line shows the average number of cases for the whole period, x =80)
Male and female cases
0
500
1.000
1.500
2.000
2.500
2005 2006 2007 2008
male
female
Figure Figure Figure Figure 13131313 NumbNumbNumbNumber of male and female er of male and female er of male and female er of male and female EP cEP cEP cEP cases in ases in ases in ases in EP(DE)EP(DE)EP(DE)EP(DE) 01/072005 to 31/12/200801/072005 to 31/12/200801/072005 to 31/12/200801/072005 to 31/12/2008
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 24
© SIDARTHa 2010 DRAFT January 2010
Mean age of cases per week
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
2005
2006
2007
2008
Figure Figure Figure Figure 14141414 Mean age of EPMean age of EPMean age of EPMean age of EP cases in cases in cases in cases in EP(DE)EP(DE)EP(DE)EP(DE) per week, 01/072005 to 31/12/2008per week, 01/072005 to 31/12/2008per week, 01/072005 to 31/12/2008per week, 01/072005 to 31/12/2008
(red line shows the overall mean age of cases for the whole period, x =53.8 )
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 25
© SIDARTHa 2010 DRAFT January 2010
Figure Figure Figure Figure 15151515 EP EP EP EP cases in cases in cases in cases in EP(DE)EP(DE)EP(DE)EP(DE) per week and age category in 2006, 2007 and 2008per week and age category in 2006, 2007 and 2008per week and age category in 2006, 2007 and 2008per week and age category in 2006, 2007 and 2008
2008
0
10
20
30
40
50
60
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52
weeks
0-25
26-64
≥65
2007
0
10
20
30
40
50
60
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52
weeks
0-25
26-64 ≥65
2006
0
10
20
30
40
50
60
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52
weeks
0-25
26-64 ≥65
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 26
© SIDARTHa 2010 DRAFT January 2010
C1, C2, C3 C1, C2, C3 C1, C2, C3 C1, C2, C3 ED(AT)ED(AT)ED(AT)ED(AT)
EARS Algorithm TIROL Hospital Data (total) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
1 13 25 37 49 61 73 85 97 109 121 133 145 157 169 181 193 205 217 229 241 253 265 277 289 301 313 325 337 349 361
Days in 2008
C1graph
C2graph
C3graph
Figure Figure Figure Figure 16161616 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n ED(AT) ED(AT) ED(AT) ED(AT) admissions in 20admissions in 20admissions in 20admissions in 2008 (unstratified baseline)08 (unstratified baseline)08 (unstratified baseline)08 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 27
© SIDARTHa 2010 DRAFT January 2010
C1, C2, C3 C1, C2, C3 C1, C2, C3 C1, C2, C3 EMD(AT)EMD(AT)EMD(AT)EMD(AT)
EARS Algorithm Tyrol Dispatch data (relevant actions) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2003
C1graph
C2graph
C3graph
Figure Figure Figure Figure 17171717 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n EMD(AT) EMD(AT) EMD(AT) EMD(AT) in 2003 (unstratified baseline)in 2003 (unstratified baseline)in 2003 (unstratified baseline)in 2003 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
EARS Algorithm Tyrol Dispatch data (relevant actions) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2004
C1graph
C2graph
C3graph
Figure Figure Figure Figure 18181818 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n EMD(AT)EMD(AT)EMD(AT)EMD(AT) in 2004 (unstratified baseline)in 2004 (unstratified baseline)in 2004 (unstratified baseline)in 2004 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 28
© SIDARTHa 2010 DRAFT January 2010
EARS Algorithm Tyrol Dispatch data (relevant actions) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2005
C1graph
C2graph
C3graph
Figure Figure Figure Figure 19191919 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n EMD(AT) EMD(AT) EMD(AT) EMD(AT) in 2005 (unstratified baseline)in 2005 (unstratified baseline)in 2005 (unstratified baseline)in 2005 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
EARS Algorithm Tyrol Dispatch data (relevant actions) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2006
C1graph
C2graph
C3graph
Figure Figure Figure Figure 20202020 C1, C2, C1, C2, C1, C2, C1, C2, C3 signals iC3 signals iC3 signals iC3 signals in Tyrol dispatch data in 2006 (unstratified baseline)n Tyrol dispatch data in 2006 (unstratified baseline)n Tyrol dispatch data in 2006 (unstratified baseline)n Tyrol dispatch data in 2006 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 29
© SIDARTHa 2010 DRAFT January 2010
EARS Algorithm Tyrol Dispatch data (relevant actions) per day
0
1
2
3
4
5
6
7
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2007
C1graph
C2graph
C3graph
Figure Figure Figure Figure 21212121 C1, C2, C3 C1, C2, C3 C1, C2, C3 C1, C2, C3 signals isignals isignals isignals in n n n EMD(AT) EMD(AT) EMD(AT) EMD(AT) in 2007 (unstratified baselin 2007 (unstratified baselin 2007 (unstratified baselin 2007 (unstratified baseline)ine)ine)ine)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
EARS Algorithm Tyrol Dispatch data (relevant actions) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2008
C1graph
C2graph
C3graph
Figure Figure Figure Figure 22222222 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n EMD(AT) EMD(AT) EMD(AT) EMD(AT) in 2008 (unstratified baseline)in 2008 (unstratified baseline)in 2008 (unstratified baseline)in 2008 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 30
© SIDARTHa 2010 DRAFT January 2010
2003
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 1 1
5 6 7 8 9 10 11 2 3 4 5 6 7 8 2 3 4 5 6 7 8
12 13 14 15 16 17 18 9 10 11 12 13 14 15 9 10 11 12 13 14 15
19 20 21 22 23 24 25 16 17 18 19 20 21 22 16 17 18 19 20 21 22
26 27 28 29 30 31 23 24 25 26 27 28 23 24 25 26 27 28 29
30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 3 1 2 3 4 5 6 7
6 7 8 9 10 11 12 4 5 6 7 8 9 10 8 9 10 11 12 13 14
13 14 15 16 17 18 19 11 12 13 14 15 16 17 15 16 17 18 19 20 21
20 21 22 23 24 25 26 18 19 20 21 22 23 24 22 23 24 25 26 27 28
27 28 29 30 25 26 27 28 29 30 31 29 30
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 1 2 3 4 5 6
6 7 8 9 10 11 12 3 4 5 6 7 8 9 7 8 9 10 11 12 13
13 14 15 16 17 18 19 10 11 12 13 14 15 16 14 15 16 17 18 19 20
20 21 22 23 24 25 26 17 18 19 20 21 22 23 21 22 23 24 25 26 27
27 28 29 30 31 24 25 26 27 28 29 30 28 29 30
31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 1 1 2 3 4 5 6
5 6 7 8 9 10 11 2 3 4 5 6 7 8 7 8 9 10 11 12 13
12 13 14 15 16 17 18 9 10 11 12 13 14 15 14 15 16 17 18 19 20
19 20 21 22 23 24 25 16 17 18 19 20 21 22 21 22 23 24 25 26 27
26 27 28 29 30 31 23 24 25 26 27 28 29 28 29 30 31
30
2004
S M T W T F S S M T W T F S S M T W T F S
1 2 3 1 2 3 4 5 6 7 1 2 3 4 5 6
4 5 6 7 8 9 10 8 9 10 11 12 13 14 7 8 9 10 11 12 13
11 12 13 14 15 16 17 15 16 17 18 19 20 21 14 15 16 17 18 19 20
18 19 20 21 22 23 24 22 23 24 25 26 27 28 21 22 23 24 25 26 27
25 26 27 28 29 30 31 29 28 29 30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 1 2 3 4 5
6 7 8 9 10 11 12 2 3 4 5 6 7 8 6 7 8 9 10 11 12
13 14 15 16 17 18 19 9 10 11 12 13 14 15 13 14 15 16 17 18 19
20 21 22 23 24 25 26 16 17 18 19 20 21 22 20 21 22 23 24 25 26
27 28 29 30 23 24 25 26 27 28 29 27 28 29 30
30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 1 2 3 4 5 6 7 1 2 3 4
4 5 6 7 8 9 10 8 9 10 11 12 13 14 5 6 7 8 9 10 11
11 12 13 14 15 16 17 15 16 17 18 19 20 21 12 13 14 15 16 17 18
18 19 20 21 22 23 24 22 23 24 25 26 27 28 19 20 21 22 23 24 25
25 26 27 28 29 30 31 29 30 31 26 27 28 29 30
S M T W T F S S M T W T F S S M T W T F S
1 2 1 2 3 4 5 6 1 2 3 4
3 4 5 6 7 8 9 7 8 9 10 11 12 13 5 6 7 8 9 10 11
10 11 12 13 14 15 16 14 15 16 17 18 19 20 12 13 14 15 16 17 18
17 18 19 20 21 22 23 21 22 23 24 25 26 27 19 20 21 22 23 24 25
24 25 26 27 28 29 30 28 29 30 26 27 28 29 30 31
31
JANUARY FEBRUARY MARCH
APRIL MAY JUNE
MARCH
JULY AUGUST SEPTEMBER
OCTOBER NOVEMBER
APRIL MAY
DECEMBER
JANUARY FEBRUARY
OCTOBER NOVEMBER
JULY AUGUST SEPTEMBER
JUNE
DECEMBER
C1 C2 C3 C2, C3 C1, C2, C3
only signal in unstratified analysis Bold signal occurred also in unstratified analysis
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 31
© SIDARTHa 2010 DRAFT January 2010
2005
S M T W T F S S M T W T F S S M T W T F S
1 1 2 3 4 5 1 2 3 4 5
2 3 4 5 6 7 8 6 7 8 9 10 11 12 6 7 8 9 10 11 12
9 10 11 12 13 14 15 13 14 15 16 17 18 19 13 14 15 16 17 18 19
16 17 18 19 20 21 22 20 21 22 23 24 25 26 20 21 22 23 24 25 26
23 24 25 26 27 28 29 27 28 27 28 29 30 31
30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 1 2 3 4 5 6 7 1 2 3 4
3 4 5 6 7 8 9 8 9 10 11 12 13 14 5 6 7 8 9 10 11
10 11 12 13 14 15 16 15 16 17 18 19 20 21 12 13 14 15 16 17 18
17 18 19 20 21 22 23 22 23 24 25 26 27 28 19 20 21 22 23 24 25
24 25 26 27 28 29 30 29 30 31 26 27 28 29 30
S M T W T F S S M T W T F S S M T W T F S
1 2 1 2 3 4 5 6 1 2 3
3 4 5 6 7 8 9 7 8 9 10 11 12 13 4 5 6 7 8 9 10
10 11 12 13 14 15 16 14 15 16 17 18 19 20 11 12 13 14 15 16 17
17 18 19 20 21 22 23 21 22 23 24 25 26 27 18 19 20 21 22 23 24
24 25 26 27 28 29 30 28 29 30 31 25 26 27 28 29 30
31
S M T W T F S S M T W T F S S M T W T F S
1 1 2 3 4 5 1 2 3
2 3 4 5 6 7 8 6 7 8 9 10 11 12 4 5 6 7 8 9 10
9 10 11 12 13 14 15 13 14 15 16 17 18 19 11 12 13 14 15 16 17
16 17 18 19 20 21 22 20 21 22 23 24 25 26 18 19 20 21 22 23 24
23 24 25 26 27 28 29 27 28 29 30 25 26 27 28 29 30 31
30 31
2006
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 1 2 3 4
8 9 10 11 12 13 14 5 6 7 8 9 10 11 5 6 7 8 9 10 11
15 16 17 18 19 20 21 12 13 14 15 16 17 18 12 13 14 15 16 17 18
22 23 24 25 26 27 28 19 20 21 22 23 24 25 19 20 21 22 23 24 25
29 30 31 26 27 28 26 27 28 29 30 31
S M T W T F S S M T W T F S S M T W T F S
1 1 2 3 4 5 6 1 2 3
2 3 4 5 6 7 8 7 8 9 10 11 12 13 4 5 6 7 8 9 10
9 10 11 12 13 14 15 14 15 16 17 18 19 20 11 12 13 14 15 16 17
16 17 18 19 20 21 22 21 22 23 24 25 26 27 28 18 19 20 21 22 23 24
23 24 25 26 27 28 29 28 29 30 31 25 26 27 28 29 30
30
S M T W T F S S M T W T F S S M T W T F S
1 1 2 3 4 5 1 2
2 3 4 5 6 7 8 6 7 8 9 10 11 12 13 3 4 5 6 7 8 9
9 10 11 12 13 14 15 13 14 15 16 17 18 19 10 11 12 13 14 15 16
16 17 18 19 20 21 22 20 21 22 23 24 25 26 17 18 19 20 21 22 23
23 24 25 26 27 28 29 27 28 29 30 31 24 25 26 27 28 29 30
30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 1 2
8 9 10 11 12 13 14 5 6 7 8 9 10 11 3 4 5 6 7 8 9
15 16 17 18 19 20 21 12 13 14 15 16 17 18 10 11 12 13 14 15 16
22 23 24 25 26 27 28 19 20 21 22 23 24 25 17 18 19 20 21 22 23
29 30 31 26 27 28 29 30 31 24 25 26 27 28 29 30
31
JANUARY
APRIL MAY JUNE
MARCHFEBRUARY
AUGUST SEPTEMBER
DECEMBEROCTOBER NOVEMBER
JULY
MAY JUNE
MARCHJANUARY FEBRUARY
APRIL
OCTOBER NOVEMBER DECEMBER
JULY AUGUST SEPTEMBER
C1 C2 C3 C2, C3 C1, C2, C3
only signal in unstratified analysis Bold signal occurred also in unstratified analysis
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 32
© SIDARTHa 2010 DRAFT January 2010
2007
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 1 2 3 1 2 3
7 8 9 10 11 12 13 4 5 6 7 8 9 10 4 5 6 7 8 9 10
14 15 16 17 18 19 20 11 12 13 14 15 16 17 11 12 13 14 15 16 17
21 22 23 24 25 26 27 18 19 20 21 22 23 24 18 19 20 21 22 23 24
28 29 30 31 25 26 27 28 25 26 27 28 29 30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 5 1 2
8 9 10 11 12 13 14 6 7 8 9 10 11 12 3 4 5 6 7 8 9
15 16 17 18 19 20 21 13 14 15 16 17 18 19 10 11 12 13 14 15 16
22 23 24 25 26 27 28 20 21 22 23 24 25 26 17 18 19 20 21 22 23
29 30 27 28 29 30 31 24 25 26 27 28 29 30
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 1
8 9 10 11 12 13 14 5 6 7 8 9 10 11 2 3 4 5 6 7 8
15 16 17 18 19 20 21 12 13 14 15 16 17 18 9 10 11 12 13 14 15
22 23 24 25 26 27 28 19 20 21 22 23 24 25 16 17 18 19 20 21 22
29 30 31 26 27 28 29 30 31 23 24 25 26 27 28 29
30
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 1 2 3 1
7 8 9 10 11 12 13 4 5 6 7 8 9 10 2 3 4 5 6 7 8
14 15 16 17 18 19 20 11 12 13 14 15 16 17 9 10 11 12 13 14 15
21 22 23 24 25 26 27 18 19 20 21 22 23 24 16 17 18 19 20 21 22
28 29 30 31 25 26 27 28 29 30 23 24 25 26 27 28 29
30 31
2008
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 1
6 7 8 9 10 11 12 3 4 5 6 7 8 9 2 3 4 5 6 7 8
13 14 15 16 17 18 19 10 11 12 13 14 15 16 9 10 11 12 13 14 15
20 21 22 23 24 25 26 17 18 19 20 21 22 23 16 17 18 19 20 21 22
27 28 29 30 31 24 25 26 27 28 29 23 24 25 26 27 28 29
30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 3 1 2 3 4 5 6 7
6 7 8 9 10 11 12 4 5 6 7 8 9 10 8 9 10 11 12 13 14
13 14 15 16 17 18 19 11 12 13 14 15 16 17 15 16 17 18 19 20 21
20 21 22 23 24 25 26 18 19 20 21 22 23 24 22 23 24 25 26 27 28
27 28 29 30 25 26 27 28 29 30 31 29 30
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 1 2 3 4 5 6
6 7 8 9 10 11 12 3 4 5 6 7 8 9 7 8 9 10 11 12 13
13 14 15 16 17 18 19 10 11 12 13 14 15 16 14 15 16 17 18 19 20
20 21 22 23 24 25 26 17 18 19 20 21 22 23 21 22 23 24 25 26 27
27 28 29 30 31 24 25 26 27 28 29 30 28 29 30
31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 1 1 2 3 4 5 6
5 6 7 8 9 10 11 2 3 4 5 6 7 8 7 8 9 10 11 12 13
12 13 14 15 16 17 18 9 10 11 12 13 14 15 14 15 16 17 18 19 20
19 20 21 22 23 24 25 16 17 18 19 20 21 22 21 22 23 24 25 26 27
26 27 28 29 30 31 23 24 25 26 27 28 29 28 29 30 31
30
JANUARY
JULY AUGUST SEPTEMBER
APRIL MAY
JULY AUGUST SEPTEMBER
JUNE
DECEMBER
MARCHFEBRUARY
OCTOBER NOVEMBER DECEMBER
MARCH
APRIL MAY JUNE
JANUARY FEBRUARY
OCTOBER NOVEMBER
C1 C2 C3 C2, C3 C1, C2, C3
only signal in unstratified analysis Bold signal occurred also in unstratified analysis
Figure Figure Figure Figure 23232323 Occurrence of signals of the C1, C2, C3 algorithm in Occurrence of signals of the C1, C2, C3 algorithm in Occurrence of signals of the C1, C2, C3 algorithm in Occurrence of signals of the C1, C2, C3 algorithm in EMD(AT)EMD(AT)EMD(AT)EMD(AT) (relevant cases) in 2003 to 2008(relevant cases) in 2003 to 2008(relevant cases) in 2003 to 2008(relevant cases) in 2003 to 2008
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 33
© SIDARTHa 2010 DRAFT January 2010
CCCC1, C2, C3 1, C2, C3 1, C2, C3 1, C2, C3 ED(DE)ED(DE)ED(DE)ED(DE)
EARS Algorithm Goeppingen data (total) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
5
1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106111 116 121 126 131 136 141146 151 156 161 166 171 176181 186
Days in 2005 (from July)
C1graph
C2graph
C3graph
Figure Figure Figure Figure 24242424 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n ED(DE) ED(DE) ED(DE) ED(DE) in 2005 (from July) (unstratified baseline)in 2005 (from July) (unstratified baseline)in 2005 (from July) (unstratified baseline)in 2005 (from July) (unstratified baseline)
(Orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
EARS Algorithm Goeppingen data (total) per day
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
5
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2006
C1graph
C2graph
C3graph
Figure Figure Figure Figure 25252525 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n ED(DE) ED(DE) ED(DE) ED(DE) in 2006 (unstratified baseline)in 2006 (unstratified baseline)in 2006 (unstratified baseline)in 2006 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 34
© SIDARTHa 2010 DRAFT January 2010
EARS Algorithm Goeppingen data (total) per day
0
1
2
3
4
5
6
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2007
C1graph
C2graph
C3graph
Figure Figure Figure Figure 26262626 C1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals iC1, C2, C3 signals in n n n ED(DE) ED(DE) ED(DE) ED(DE) in 2007 (unstratified basin 2007 (unstratified basin 2007 (unstratified basin 2007 (unstratified baseline)eline)eline)eline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
EARS Algorithm Goeppingen data (total) per day
0
1
2
3
4
5
6
7
8
1 12 23 34 45 56 67 78 89 100 111 122 133 144 155 166 177 188 199 210 221 232 243 254 265 276 287 298 309 320 331 342 353 364
Days in 2008
C1graph
C2graph
C3graph
Figure Figure Figure Figure 27272727 C1, C2, C3 signals on Goeppingen data in 2008 (unstratified baseline)C1, C2, C3 signals on Goeppingen data in 2008 (unstratified baseline)C1, C2, C3 signals on Goeppingen data in 2008 (unstratified baseline)C1, C2, C3 signals on Goeppingen data in 2008 (unstratified baseline)
(orange and green line mark the threshold of C1 and C2; blue line marks the threshold C3)
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 35
© SIDARTHa 2010 DRAFT January 2010
2005
S M T W T F S S M T W T F S S M T W T F S
1 2 1 2 3 4 5 6 1 2 3
3 4 5 6 7 8 9 7 8 9 10 11 12 13 4 5 6 7 8 9 10
10 11 12 13 14 15 16 14 15 16 17 18 19 20 11 12 13 14 15 16 17
17 18 19 20 21 22 23 21 22 23 24 25 26 27 18 19 20 21 22 23 24
24 25 26 27 28 29 30 28 29 30 31 25 26 27 28 29 30
31
S M T W T F S S M T W T F S S M T W T F S
1 1 2 3 4 5 1 2 3
2 3 4 5 6 7 8 6 7 8 9 10 11 12 4 5 6 7 8 9 10
9 10 11 12 13 14 15 13 14 15 16 17 18 19 11 12 13 14 15 16 17
16 17 18 19 20 21 22 20 21 22 23 24 25 26 18 19 20 21 22 23 24
23 24 25 26 27 28 29 27 28 29 30 25 26 27 28 29 30 31
30 31
2006
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 1 2 3 4
8 9 10 11 12 13 14 5 6 7 8 9 10 11 5 6 7 8 9 10 11
15 16 17 18 19 20 21 12 13 14 15 16 17 18 12 13 14 15 16 17 18
22 23 24 25 26 27 28 19 20 21 22 23 24 25 19 20 21 22 23 24 25
29 30 31 26 27 28 26 27 28 29 30 31
S M T W T F S S M T W T F S S M T W T F S
1 1 2 3 4 5 6 1 2 3
2 3 4 5 6 7 8 7 8 9 10 11 12 13 4 5 6 7 8 9 10
9 10 11 12 13 14 15 14 15 16 17 18 19 20 11 12 13 14 15 16 17
16 17 18 19 20 21 22 21 22 23 24 25 26 27 18 19 20 21 22 23 24
23 24 25 26 27 28 29 28 29 30 31 25 26 27 28 29 30
30
S M T W T F S S M T W T F S S M T W T F S
1 1 2 3 4 5 1 2
2 3 4 5 6 7 8 6 7 8 9 10 11 12 13 3 4 5 6 7 8 9
9 10 11 12 13 14 15 13 14 15 16 17 18 19 10 11 12 13 14 15 16
16 17 18 19 20 21 22 20 21 22 23 24 25 26 17 18 19 20 21 22 23
23 24 25 26 27 28 29 27 28 29 30 31 24 25 26 27 28 29 30
30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 1 2
8 9 10 11 12 13 14 5 6 7 8 9 10 11 3 4 5 6 7 8 9
15 16 17 18 19 20 21 12 13 14 15 16 17 18 10 11 12 13 14 15 16
22 23 24 25 26 27 28 19 20 21 22 23 24 25 17 18 19 20 21 22 23
29 30 31 26 27 28 29 30 24 25 26 27 28 29 30
31
JULY AUGUST SEPTEMBER
OCTOBER NOVEMBER DECEMBER
MARCH
APRIL MAY JUNE
JANUARY FEBRUARY
DECEMBEROCTOBER NOVEMBER
JULY AUGUST SEPTEMBER
C1 C2 C3 C2, C3 C1, C2, C3
only signal in unstratified analysis Bold signal occurred also in unstratified analysis
APPENDIX - Developing Algorithms for Early Public Health Threat Detectionin Europe 36
© SIDARTHa 2010 DRAFT January 2010
2007
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 1 2 3 1 2 3
7 8 9 10 11 12 13 4 5 6 7 8 9 10 4 5 6 7 8 9 10
14 15 16 17 18 19 20 11 12 13 14 15 16 17 11 12 13 14 15 16 17
21 22 23 24 25 26 27 18 19 20 21 22 23 24 18 19 20 21 22 23 24
28 29 30 31 25 26 27 28 25 26 27 28 29 30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 5 1 2
8 9 10 11 12 13 14 6 7 8 9 10 11 12 3 4 5 6 7 8 9
15 16 17 18 19 20 21 13 14 15 16 17 18 19 10 11 12 13 14 15 16
22 23 24 25 26 27 28 20 21 22 23 24 25 26 17 18 19 20 21 22 23
29 30 27 28 29 30 31 24 25 26 27 28 29 30
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 7 1 2 3 4 1
8 9 10 11 12 13 14 5 6 7 8 9 10 11 2 3 4 5 6 7 8
15 16 17 18 19 20 21 12 13 14 15 16 17 18 9 10 11 12 13 14 15
22 23 24 25 26 27 28 19 20 21 22 23 24 25 16 17 18 19 20 21 22
29 30 31 26 27 28 29 30 31 23 24 25 26 27 28 29
30
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 6 1 2 3 1
7 8 9 10 11 12 13 4 5 6 7 8 9 10 2 3 4 5 6 7 8
14 15 16 17 18 19 20 11 12 13 14 15 16 17 9 10 11 12 13 14 15
21 22 23 24 25 26 27 18 19 20 21 22 23 24 16 17 18 19 20 21 22
28 29 30 31 25 26 27 28 29 30 23 24 25 26 27 28 29
30 31
2008
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 1
6 7 8 9 10 11 12 3 4 5 6 7 8 9 2 3 4 5 6 7 8
13 14 15 16 17 18 19 10 11 12 13 14 15 16 9 10 11 12 13 14 15
20 21 22 23 24 25 26 17 18 19 20 21 22 23 16 17 18 19 20 21 22
27 28 29 30 31 24 25 26 27 28 29 23 24 25 26 27 28 29
30 31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 3 1 2 3 4 5 6 7
6 7 8 9 10 11 12 4 5 6 7 8 9 10 8 9 10 11 12 13 14
13 14 15 16 17 18 19 11 12 13 14 15 16 17 15 16 17 18 19 20 21
20 21 22 23 24 25 26 18 19 20 21 22 23 24 22 23 24 25 26 27 28
27 28 29 30 25 26 27 28 29 30 31 29 30
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 5 1 2 1 2 3 4 5 6
6 7 8 9 10 11 12 3 4 5 6 7 8 9 7 8 9 10 11 12 13
13 14 15 16 17 18 19 10 11 12 13 14 15 16 14 15 16 17 18 19 20
20 21 22 23 24 25 26 17 18 19 20 21 22 23 21 22 23 24 25 26 27
27 28 29 30 31 24 25 26 27 28 29 30 28 29 30
31
S M T W T F S S M T W T F S S M T W T F S
1 2 3 4 1 1 2 3 4 5 6
5 6 7 8 9 10 11 2 3 4 5 6 7 8 7 8 9 10 11 12 13
12 13 14 15 16 17 18 9 10 11 12 13 14 15 14 15 16 17 18 19 20
19 20 21 22 23 24 25 16 17 18 19 20 21 22 21 22 23 24 25 26 27
26 27 28 29 30 31 23 24 25 26 27 28 29 28 29 30 31
30
OCTOBER NOVEMBER DECEMBER
APRIL MAY JUNE
JULY AUGUST SEPTEMBER
OCTOBER NOVEMBER DECEMBER
JANUARY FEBRUARY MARCH
APRIL MAY JUNE
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C1 C2 C3 C2, C3 C1, C2, C3
only signal in unstratified analysis Bold signal occurred also in unstratified analysis
Figure Figure Figure Figure 28282828 Occurrence of signals of the C1, C2, C3 algorithm in Occurrence of signals of the C1, C2, C3 algorithm in Occurrence of signals of the C1, C2, C3 algorithm in Occurrence of signals of the C1, C2, C3 algorithm in ED(DE) ED(DE) ED(DE) ED(DE) in 2005in 2005in 2005in 2005----2008200820082008