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Migration, Mobility and Malaria

Research on Migrants’ Vulnerability to Malaria and Epidemiology of Artemisinin-Resistant Malaria in Binh Phuoc Province, Viet Nam

Research of IOM - IMPE HCM - WHO

Presented by Vũ Mạnh Lợi 9/8/2016

1. Introduction 2. Research questions 3. Research methodology

• Type of migration status • Migration status by residence period • Research limitation

4. Research outcomes Knowledge, Attitude and Practices (KAP) Survey

• Background • Access to malaria services • Malaria knowledge • Malaria control and prevention practice • Other risky behaviors • What to do when contracting malaria?

In- depth study • Geographical distribution of respondents by migration status • Housing • Work sites • Residence registration and service access level • Malaria status • Sleeping on “ray”

5. Conclusion and recommendations

1. Introduction

• Progress in reducing malaria incidence and mortality rate in 2013 and 2014 tends to be stagnant.

• Artemisinin resistant (identified by slow parasite cleaning phenomenon) has notably been increasing from 2009 to date

Map 1: Most active malaria areas and migration status in Vietnam

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

2009 2010 2011 2012 2013

Per t

hous

and

popu

latio

n

Figure 1a. Malaria cases per 1,000 people in 2009-2013 in Bình Phước (Annex 3, Action Plan and Program on Malaria Prevention, Control and Treatment for 2015-2020,

MOH 2014)

Binh Phuoc Whole coutry

• Most malaria cases were detected in Bu Gia Map district with 683 cases in 2014 (43% of total malaria cases in Binh Phuoc province) and 217 cases in Bu Dang district (13.7% of total malaria cases in Binh Phuoc province) (Malaria Prevention and Control Center 2014)

2. Research questions

• Who are migrant, mobile people in Binh Phuoc province? Where do they come from and go to? How long do they live in Binh Phuoc? What are they doing there? Where in the province are they living? How can this group of population be categorized?

• How and why migrant, mobile people are more vulnerable than local residents?

3. Research methodology • Knowledge, Attitude and Practices (KAP) survey among

MMP in 6 communes (3 districts) of Binh Phuoc Province (N=2005);

• In-depth study with 300 persons in DakO commune: – 150 persons were randomly selected from 150 households in

the commune; – 50 patients were selected from the CHC patient list; – 100 migrants were working in the commune. – 3 group discussions – 35 in-depth interviews – Analysis of current documents of the commune

• Using GPS equipment for mobility mapping (in both KAP and in-depth study)

Type of migration status

• Residence type in Vietnam: KT1 for permanent residents; KT2,3,4 for temporary residents (The Residence Registration Law)

• The temporary residence status is not suitable in the malaria context

• The temporary residence status does not include “mobile population” (due to very short residence period)

Migration status by residence period • People with continuous residence of under or

equal to 6 months are in the “mobile” group; • People with continuous residence of over 6

months and under 1 year are in the “short-term migration” group;

• People with continuous residence of over 1 year and under 5 years are in the “long-term migration” group;

• People born in the local area or with continuous residence of over 5 years are in the “local resident” group.

Research limitation

• Selection bias: can only access people working in the commune at the time of the survey (from Dec/2014 to Mar/2015 with KAP survey and Aug/2015 with in-depth study).

• MMP in Binh Phuoc is changing significantly at different times of the year. The survey time may not be the best time for the study.

• Some MMPs are living in hard to reach areas, for example working in forest.

• Sampling error: respondents may not be an MMP member. • In-depth study sample size is small causing difficulty in using

detailed data.

4. RESEARCH OUTCOMES: Knowledge, Attitude and Practices

(KAP) Survey

Distribution of residential clusters at survey area (KAP survey)

General context Figure 1: Migrant origin – birthplace and previous place of residence

Source: IOM ca lculations, based on the IMPE HCMC KAP survey 2014–2015.

18.1

9.414.0

2.0

30.6

8.6

15.9

1.4

14.9

6.09.1

4.8

39.9

12.0 12.9

.451015202530354045

Northernmidlands

andmountain

areas

Red RiverDelta

NorthernCentral

andCentralcoastal

area

CentralHighlands

BinhPhuoc

Province

South East MekongRiverDelta

Cambodia

%

Birth place (N=2005) Previous place of residence (N=2005)

3

Map 6: Provinces in Viet Nam with malaria prevalence and flows of migrants to Binh Phuoc

Access to Malaria Services Figure 1: Distance to the nearest health facility


6.0 9.5 10.1 9.0

12.5

23.8

42.431.6

25.6

20.6

24.4 48.655.8

46.0

23.110.8

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Mobilemigrants(N=480)

Short-termmigrants (N=63)

Long-termmigrants(N=1250)

Local residents(N=212)

Over 10 km

Between 5 and 10 km

Between 1 and 5 km

Less than 1 km

4

Figure 1: Respondents who reported living in a village with a village health worker by ethnicity of respondent

Source: IOM ca lculations , based on the IMPE HCMC KAP survey 2014–2015

6049.7

45.2 47.6

70.1 73.7

61.9

45.9

01020304050607080

Kinhethnicity(N=325)

Ethnicminority(N=155)

Kinhethnicity

(N=42)


Kinhethnicity(N=756)


Kinhethnicity

(N=42)


Mobile migrants Short-term migrants Long-term migrants Local residents

%5

Figure 1: Source of mosquito net by migration status and sex (N=1989)


26.7

37.429.8

43.8 40.948.8 50.0

75.883.4

76.9 74.568.8

83.0 80.573.2 70.5

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Men(N=326)

Women(N=147)

Men(N=47)

Women(N=16)

Men(N=805)

Women(N=441)

Men(N=112)

Women(N=95)


%

Provided by the NMCP Bought at the market

6

The commune provides ITNs for free, twice a year. But the material used to make the net is not good, it’s not soft and the netting is so big that small mosquitoes can get inside. We used to use it for catching fish..

24-year-old man, Stieng ethnic group. Interview, in-depth study.

Malaria knowledge

• Regression analysis shows that malaria knowledge will be better in case of: – Higher level of education; – Having health workers in the village; – Local and long-term residents have better malaria knowledge than mobile or

short-term migration people.

Figure 1: Proportion of respondents who have ever heard of malaria by sex, education and ethnicity

Source: IOM ca lculations , based on the IMPE HCMC KAP survey 2014–2015.

88 81 7694 88 8183 81

71

91 91

67

96 93 91 98 97 9292 88 8797 98

88

0

20

40

60

80

100

120

Men Women Primaryeducation or

less

Secondary ormore

Kinh Ethnicminority

Sex Education Ethnicity

%

Mobile migrants (N=480) Short-term migrants (N=63)

Long-term migrants (N=1250) Local residents (N=212)

7

Table 6: Proportion of respondents who have heard of malaria who correctly identified facts about malaria (N=1840) (%)

Correct answer Mobile migrants Short-term

migrants Long-term migrants Local residents

Avg. Men (N=292)

Women (N=121)

Men (N=39)

Women (N=13)

Men (N=772)

Women (N=412)

Men (N=105)

Women (N=86)

Only mosquito bites cause malaria infection

79.5 73.6 64.1 61.5 76.2 82 81.9 76.7 77.8

Malaria can be fatal if not treated properly

89 81.8 89.7 61.5 91.7 87.4 85.7 81.4 88.6

Everybody is at risk 78.1 71.9 53.8 61.5 51.4 43.4 63.8 57 56.3 Symptoms of malaria infection (correctly identified the two most common symptoms)

65.8 62 53.8 30.8 75.1 69.4 63.8 46.5 68.8

Malaria is preventable 89.4 80.2 76.9 69.2 88.5 87.1 78.1 73.3 86.1

Correctly identified at least four of these five facts

75 68.6 53.8 38.5 69.7 66.3 67.6 61.6

68.6

Source: IOM calculations, based on the IMPE HCMC KAP survey 2014–2015.

Table 8: Knowledge of possible malaria-prevention methods by migration status and by sex among respondents who knew that malaria can be prevented (N=1597) (%) (multiple-choice question)

Mobile migrants Short-term migrants

Long-term migrants Local residents

Men (N=263)

Women (N=98)

Men (N=30)

Women (N=9)

Men (N=687)

Women (N=365)

Men (N=82)

Women (N=63)

Mosquito nets 97 99 100 100 97.2 97.8 90.2 95.2

Long-sleeved clothes 8.4 9.2 10 11.1 17.8 10.4 8.5 11.1

Burn leaves to create smoke 8.4 4.1 10 11.1 13.8 10.1 15.9 19

Insecticides 28.5 44.9 20 11.1 21.8 20 20.7 9.5

Clear bushes around house 16.7 13.3 23.3 55.6 35.2 24.9 23.2 12.7

Clear the corners of the house to avoid encouraging mosquitoes 8.4 4.1 13.3 33.3 15 11.5 12.2 9.5

Source: IOM calculations, based on the IMPE HCMC KAP survey 2014–2015. Note: Respondents were given a range of (correct) options, of which they could choose more than one, including

“I don’t know” – only nine respondents chose this last option.

Incorrect knowledge about malaria: data from the in-depth study

• I don’t think you get malaria from mosquito bites, but I don’t know how you do get it ... I used to live and eat in the forest, drink non-boiled water and have a lot of mosquito bites, but I didn’t catch anything. Now, maybe, because we buy food at the market – food at the market nowadays has a lot of fertilizers and pesticides on it … Now we drink boiled water, we eat well-cooked food, but we get malaria. I don’t know who’s at high-risk, whoever gets it gets it, it’s like playing the lottery.

A locally resident man, aged 54, member of the Stieng ethnic minority, who had had malaria more than one year prior to the interview.

• Here everybody had malaria, [but] recently local people are more likely to get it… The ethnic minority people call it “dengue” … I’ve had malaria two or three times since the beginning of the year, I’m not sure whether it was already in my body or somewhere in the air, it’s called “super virus flu” … malaria and super virus flu are the same.

Male village leader. (Focus-group discussion among village leaders)

Malaria control and prevention practice Table 9: Malaria-prevention methods used by respondents, by migration status and by sex (%)

(multiple-choice question)


Men (N=331)

Women (N=149)

Men (N=47)

Women (N=16)

Men (N=807)

Women (N=443)

Men (N=114)

Women (N=98)

Mosquito nets 97.6 98.7 100 93.8 99.5 98.9 97.4 96.9

Mosquito coil 22.4 28.2 14.9 6.3 19.8 16 14.9 17.3

Sleeping bags 6.3 2.7 6.4 0 4.2 0.9 5.3 1

Fire and smoke 6.3 4 10.6 0 10.2 7.9 14 14.3

Mosquito repellent 5.4 2 2.1 0 8.1 5 3.5 1

Close windows and doors 0.6 0 4.3 0 2.7 1.4 3.5 1

Use window nets 0.3 0 2.1 0 0.9 0.7 0 1

Do nothing 3.9 8.7 10.6 0 3.7 3.4 5.3 9.2

Source: IOM calculations, based on the IMPE HCMC KAP survey 2014–2015. Note: A number of respondents chose “other”: 25 mobile migrants, 6 short-term migrants, 74 long-term migrants

and 20 local residents. These local residents said they “didn’t know”. The other respondents had varied responses, saying that they “didn’t know” or cited: food hygiene (only long-term migrants mentioned this; it is incorrect); killing mosquitoes with an electric racket; killing mosquito larvae; removing stagnant water sources; using an electric fan to keep mosquitoes away; using a blanket as a cover (this is not an effective method); using a hammock with a net; and avoiding sleeping in “ray”.

Other risky behaviors

I get most mosquito bites during cassava season, when I go to work in the forest and sleep in the "ray", going home only once a week. From my home to my workplace is a long way. I don’t take repelling incense sticks, insect repellent spray or a mosquito net. I only use a hammock and blanket. I don't like to use cream because I can’t get used to it and anyway I can’t afford it. At home I use a mosquito net, which is set up all day long.

22-year-old man, Stieng ethnic minority. Interview, in-depth study.

• When I work during cassava season, I get a lot of mosquito bites. There are a lot of mosquitoes at the times when we work and sleep. At the worksite, people burn fires to create smoke, but it doesn’t help much. Digging cassava usually starts at around 4am when there are a lot of mosquitoes, and many men keep their upper body naked while they work in order to feel cool, because the weather is very hot. I don’t think mosquito bites kill, so I let it go..

22-year-old man, Stieng ethnic minority. Interview, in-depth study.

Table 10: In-depth study: Proportion of respondents who use malaria-prevention methods when they sleep in the forest (N=131) (%) (multiple-choice question)

Mobile migrants (N=14)

Short-term migrants

(N=17)

Long-term migrants

(N=13)

Local residents

(N=87)

Untreated mosquito net 21.4 52.9 38.5 29.9

ITN 50.0 52.9 61.5 39.1

Insect repellent cream 0 5.9 7.7 3.4

Other (including, as specified by respondents): canvas, hammock with/without net, repelling incense sticks

35.7 17.6 15.4 14.9

Source: IOM calculations, based on the IMPE HCMC in-depth survey 2015. Note: For this question (3.2 of the in-depth study), for each method respondents were asked first whether they used it and, if they answered yes, how often (always/sometimes). 1 mobile migrant, 1 short-term migrant and 17 local residents said that they did not use any prevention methods.

Table 11: Ownership and use of mosquito nets by migration status and sex (%)


Men (N=331)

Women (N=149)

Men (N=47)

Women (N=16)

Men (N=807)

Women (N=443)

Men (N=114)

Women (N=98)

Family has [at least] one mosquito net1 98.5 98.7 100 100 99.8 99.5 98.2 96.9

Those respondents who owned one or more mosquito nets were asked to choose from the following options (multiple-choice question):

Use non-insecticide-treated net(s) 77.9 71.8 66 50 46.2 41.3 43 28.6

Use net(s) treated with insecticide by a health worker 16.9 24.8 23.4 25 48.7 50.8 33.3 38.8

Use ITN(s) provided by the commune 13.3 15.4 19.1 43.8 30.9 35.2 42.1 66.3

Use hammock(s) with net(s) 12.1 0.7 0 6.3 8.4 4.1 6.1 1


What to do when contracting malaria? Figure 1: How long after contracting malaria did you seek treatment? – by gender and ethnicity

(N=539)

Source: IOM ca lculations , based on the IMPE HCMC KAP survey 2014–2015.

51.6

35.3

58.0

31.0

59.9

61.4

65.2

48.9

33.9

52.9

34.0

44.8

27.9

25.7

24.8

33.3

6.5

11.8

2.0

17.2

8.9

9.9

8.5

10.6

8.1

6.0

6.9

3.3

3.0

1.6

7.1

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Men (N=62)

Women (N=17)

Kinh ethnicity (N=50)

Ethnic minority (N=29)

Men (N=359)

Women (N=101)



Curr

ent m

igra

nts

(N=7

9)Lo

ng-t

erm

mig

rant

s(N

=460

)

1 day 2 to 3 days 4 or more days Don't know/No answer

8

Table 1: Place of treatment by ethnicity (N=539) (%)

Current migrants Long-term residents

Kinh (N=50)

Ethnic minority (N=29) Kinh (N=319)


Commune health center or clinic 88 72.4 93.1 88.7

Local health worker 8 10.3 26.6 14.2

Traditional healer 0 0 0 0

Pharmacy 2 3.4 4.4 4.3

Private facility 8 13.8 4.1 3.5


Figure 1: Proportion of malaria patients who completed the full course of malaria medication by sex and by ethnicity (N=529)

Source: IOM ca lculations , based on the IMPE HCMC KAP survey 2014–2015

90.0

75.0

89.8

81.5

93.3 91.8 93.990.7

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Men Women Kinh ethnicity Ethnic minority

%

Current migrants (N values: Men=60; Women=16; Kinh ethnicity=49; Ethic minority=27)

Long-term migrants (N values: Men=356; Women=97; Kinh ethnicity=313; Ethnic minority=140)

9

RESEARCH OUTCOMES : In-depth study

Map 7: Geographical distribution of in-depth study respondents by migration status

Housing Figure 1: Location of primary and secondary residences

Source: IOM ca lculations , based on the IMPE HCMC in-depth survey 2015.

60.8

29.420.0

72.0

24.236.4

53.4

12.6

17.6

23.5

16.0

0.0

33.318.2

31.9

23.0

21.6

37.364.0

12.0 42.4

6.1

14.7

20.9

9.8 16.0

39.4 43.5

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Primaryresidence

Secondaryresidence

Primaryresidence

Secondaryresidence

Primaryresidence

Secondaryresidence

Primaryresidence

Secondaryresidence

Mobile migrants(N=51)

Short-term migrants(N=25)

Long-term migrants(N=33)

Local residents (N=191)

In a residential area In "ray" In a forested area No secondary residence

12

Figure 1: Proportion of respondents who are joined by at least one family member when at their secondary residence (N=240)

Source: IOM ca lculations , based on the IMPE HCMC in-depth survey 2015

89.6 91.7

63.3 63.8

0

10

20

30

40

50

60

70

80

90

100

Mobile migrants(N=48)

Short-term migrants(N=24)

Long-term migrants(N=30)

Local residents(N=138)

%

13

Figure 1: Primary and secondary housing structure by migration status (N=299)

Source: IOM ca lculations, based on the IMPE HCMC in-depth survey 2015.

37

23

40

52

33 35 34

2327

55

48

19

9

20

7

48

33

1812

24

52

30

47

18

25 5 6

10 11

15

1010

20

30

40

50

60

Primaryresidence

(N=51)

Secondaryresidence

in/nearforest(N=44)

Primaryresidence

(N=25)

Secondaryresidence

in/nearforest(N=21)

Primaryresidence

(N=33)

Secondaryresidence

in/nearforest(N=20)

Primaryresidence(N=190)

Secondaryresidence

in/nearforest

(N=107)


%

Primitive structure Temporary structure Decent structure Solid structure Other

14

WORK SITES Table 16: Location of main workplace in the 12 months prior to the survey by migration status and

gender (%)



Women (N=18)

Men (N=33)

Women (N=10)

Men (N=15)

Women (N=12)

Men (N=21)

Women (N=60)

Men (N=131)

Work within the commune only 27.8 21.2 10 33.3 66.7 81 90 74.8

Work in another commune within the district 33.3 51.5 20 20 0 0 1.7 3.1

Work in another district within the province 5.6 6.1 0 0 0 4.8 0 0.8

Work in another province 22.2 9.1 20 13.3 0 0 0 0

Work in Cambodia 0 0 0 0 0 0 0 1.5

Work in another country 0 0 0 0 0 0 0 1.5

Source: IOM calculations, based on the IMPE HCMC in-depth survey 2015. Note: This data is from question 3.1 on respondents’ main job per month over the last 12 months. The options

were mutually exclusive. Not all respondents provided enough information to establish their main workplace.

Table 17: Location of main workplace in the 12 months prior to the survey by migration status and ethnicity (%)



Kinh (N=9)


Kinh (N=8)


Kinh (N=22)


Kinh (N=50)


Work within the commune only 44.4 19 62.5 5.9 72.7 81.8 84 78

Work in another commune within the district 11.1 52.4 12.5 23.5 0 0 2 2.8

Work in another district within the province 0 7.1 0 0 4.5 0 2 0

Work in another province 22.2 11.9 0 23.5 0 0 0 0

Work in Cambodia 0 0 0 0 4.5 0 6 2.8

Work in another country 0 0 0 0 0 0 0 1.4

Source: IOM calculations, based on the IMPE HCMC in-depth survey 2015. Note: This data is from question 3.1 on respondents’ main job per month over the last 12 months. The options

were mutually exclusive. Not all respondents provided enough information to establish their main workplace.

Figure 1: Forested areas – Location of workplace in forested areas in the 12 months prior to the survey by migration status and ethnicity (N=298)

Source: IOM ca lculations , based on the IMPE HCMC in-depth survey 2015.

77.8

70.7

62.5

17.6

61.9

54.5

52

55.3

22.2

29.3

37.5

82.4

38.1

45.5

48

44.7

0 20 40 60 80 100









Mob

ilem

igra

nts

Shor

t-te

rmm

igra

nts

Long

-ter

mm

igra

nts

Loca

lre

side

nts

%

Always worked outside forested areas Worked in forested areas all or some of the time

15

Figure 1: Forested areas – Location of workplace in forested areas in the 12 months prior to the survey by migration status and sex (N=298)


72.7

70.6

33.3

30

57.1

63.6

52.7

58.3

27.3

29.4

66.7

70

42.9

36.4

47.3

41.7

0 20 40 60 80 100

Men (N=33)

Women (N=17)

Men (N=15)

Women (N=10)

Men (N=21)

Women (N=11)

Men (N=131)

Women (N=60)

Mob

ilem

igra

nts

Shor

t-te

rmm

igra

nts

Long

-ter

mm

igra

nts

Loca

l res

iden

ts

%

Always worked outside forested areas Worked in forested areas all or some of the time

6

Household registration status and access to services Table 1: Household registration status by migration status (people) (%)

Mobile migrants (N=51)

Short-term migrants (N=25)

Long-term migrants (N=33)

Local residents (N=191)

Total (N=300)

KT1 2 (3.9) 2 (8.0) 12 (36.4) 186 (97.4) 202 (67.3)

KT2 0 (0.0) 3 (12.0) 7 (21.2) 2 (1.0) 12 (4.0)

KT3 0 (0.0) 4 (16.0) 8 (24.2) 1 (0.5) 13 (4.3)

KT4 14 (27.5) 4 (16.0) 6 (18.2) 0 (0.0) 24 (8.0)

Not registered 35 (68.6) 12 (48.0) 0 (0.0) 2 (1.0) 49 (16.3)

Total 51 (100.0) 25 (100.0) 33 (100.0) 191 (100.0) 300 (100.0)

Source: IOM calculations, based on the IMPE HCMC in-depth survey 2015.

Figure 1: Proportion of respondents who received free ITNs by registration status (% of total in each registration category) (N=291)


90.1

83.3

53.8

82.6

53.7

0

10

20

30

40

50

60

70

80

90

100

KT1 (N=202) KT2 (N=12) KT3 (N=13) KT4 (N=23) Not registered(N=41)

%17

Malaria incidence status Figure 1: Proportion of respondents who reported contracting malaria in the five years prior to the

survey by age group and sex


Note: These data are based on responses relating to the most recent malaria incident. The data include the sub-sample of 50 malaria patients obtained from the CHC l ist. The analysis was a lso run on the data without the sub-sample and the resul ts were not dis tinguishable. N=300.

32.9

55.2

49.1

22.2

7.1

25.0

0

10

20

30

40

50

60

Aged 15-29 (N values:Men=76; Women=36)

Aged 30-39 (N values:Men=67; Women=28)

Aged 40 or over (N values:Men=57; Women=36)

%

Men (N=200) Women (N=100)

18

Figure 1: Proportion of respondents who reported contracting malaria in the five years prior to the survey by ethnicity and sex

Source: IOM ca lculations, based on the IMPE HCMC in-depth survey 2015. Note: The data include the sub-sample of 50 malaria patients obtained from the CHC l ist. The analysis was also run

on the data without the sub-sample and the results were not distinguishable. N=300.

50.7

20.0

42.0

18.8

0

10

20

30

40

50

60

Men (N=200) Women (N=100)

%

Kinh ethnicity (N values: Men=69; Women=20)

Ethnic minority (N values: Men=131; Women=80)

19

Map 10: Geographical distribution of respondents who contracted malaria between 2010 and 2015 by ethnicity

Figure 20: Proportion of patients who reported contracting malaria in the five years prior to the survey by working environment and migration status (N=296)


Note: The data include the sub-sample of 50 malaria patients obtained from the CHC list, and therefore risks make the sample biased towards malaria incidence among the long-term migrants and local residents. N=296

13.9

50

36.8 38.2

28.6

23.5

46.2 47.1

0

10

20

30

40

50

60

Mobile migrants (Nvalues: Outside

forest=36; Insideforest=14)

Short-term migrants (Nvalues: Outside forest=8;

Inside forest=17)

Long-term migrants (Nvalues: Outside

forest=19; Insideforest=13)

Local residents (N values:Outside forest=102;

Inside forest=87)

%

Always worked outside forested areas Worked in forested areas some or all of the time

Figure 21: Proportion of respondents who reported contracting malaria in the five years prior to the survey by time spent at a residence in a forested area (N=298)


Note: The data include the sub-sample of 50 malaria patients obtained from the CHC list. N=298.

33.3

36

39

30

31

32

33

34

35

36

37

38

39

40

Never spent time at aresidence in a forested area

(N=63)

Spent (cumulatively) < 6months at a residence in a

forested area (N=89)

Spent (cumulatively) > 6months at a residence in a

forested area (N=146)

%

Sleeping on “ray”

Map 11: Travel from current/previous work sites by malaria infection

5. Conclusion

•Mobile and short-term migrants are more than three times less likely than local residents to have heard of malaria.

•Live further away from health facilities •Being less likely to have access to ITNs.

Services access

•Short-term migrants have a much lower level of knowledge about malaria than other respondents Knowledge

•“Short-term migrants” wait longer than “long-term residents” before seeking treatment for malaria.

Health care seeking behavior

•More likely living in primitive or temporary structures and nearly forest

•More likely sleeping on Ray and in forest Exposure

Risk for MMP

However…

• “Local residents” also have a high rate of movement (44% having alternative house on “ray”/in forest), therefore malaria risk is also high and needs to be paid attention to.

• Both local resident and MMP groups still face issues regarding knowledge, attitude, behavior, related to malaria prevention (lack of knowledge, low level of education, bad habit, etc.).

5. Conclusion

• People with lower levels of education are less likely than those with higher levels of education to be knowledgeable

• Ethnic minority people tend to wait longer before seeking treatment when they experience malaria symptoms, and are less likely to complete the full course of prescribed treatment, than people belonging to the majority Kinh ethnic group;

• Men are more exposed than women to malaria since they travel more often to forests and border areas.

• People aged 30 years and above are more likely to have experienced malaria in the previous five years than younger people

• People who earn within the middle-income range (between 3,000,000 and 5,000,000 VND/month) are more likely to travel to forests or border areas and are therefore more at risk than those in other income brackets.

5. Conclusion Other risk factors

5. Recommendations • Increase behavior change communication programs for both

migrant and local residents, taking into account the specific characteristics of each groups

• Raise awareness of the presence and role of village health workers.

• Adapt malaria prevention services in line with the survey results: provide different sizes of ITNs (individual and family) and improve ITN quality; distribute or subsidize the cost of hammock with nets.

• Improve routine monitoring record templates and processes to collect disaggregated data at the community health centre level, including migrant status; registration status; permanent and current address; mobility patterns (frequency of stay in forest per year); place where malaria was contracted; intention to move during treatment.

5. Recommendations • Formulate a long-term malaria-control strategy targeting

migrants and mobile people at the national and provincial levels, as well as the commune level – The health sector needs to work closely with local governments, social

mass organizations, local agencies (schools, border soldiers and the private sector, etc.); there needs to be more synchronous coordination mechanism;

• Research recommendations • Apply and improve the research methodology piloted in this research,

especially the MMP classification method in other provinces with similar context. – Conduct further research on the link between: i) malaria and migration

status (MMP groups compared to local residents) and ii) vulnerability to malaria and occupation.

– Conduct research to investigate the vulnerability of specific high risk groups of people for whom traditional protection methods are not fully effective (cassava workers and those, especially women, who bathe in streams), to identify ways to protect them.

Thank you!

migration, mobility and malaria · migration, mobility and malaria ... conclusion and...

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