Knowledge attitude & Practice survey protocol

Table of Content

Table of Content1

1Justification2

2Current Status / Available Information2

3Objectives3

4Methodology3

4.1Qualitative Data Collection3

4.1.1Sampling, Data Collection & Analysis4

4.2KAP Survey4

4.2.1Study Design5

4.2.2Sample Design5

4.2.2.1First stage sampling procedure: cluster selection6

4.2.2.2Second stage sampling procedure: household selection6

4.2.2.2.1Segmentation6

4.2.2.3Sample size determination6

5Indicators10

6Personnel & Collaboration12

7Training12

8Fieldwork Plan13

9Data Collection and Supervision13

9.1Field Testing of Instrument13

9.2Field Data Collection13

10Data Quality Control and Data Entry14

10.1Data quality control14

10.2Data entry15

11Analysis and Report Writing15

12Dissemination15

13Anticipated limitations and potential biases15

Annex 1: Implementation timeline17

References18

1. Justification

The humanitarian crisis in North-East Nigeria has become protracted, with the populace bearing the brunt of the conflict that has resulted in widespread displacement, destroyed infrastructure and collapsed basic social services. Threats of attacks by non-state armed groups and restrictions in movements continue to have negative impacts on trade, livelihoods and markets, leaving a substantial proportion of the population relying on humanitarian assistance.[footnoteRef:2] As at November 2019, 2,035,232 people are still displaced in the three most affected states - Borno, Adamawa and Yobe (BAY) States[footnoteRef:3] – with 80 percent of the displaced population being women and children.[footnoteRef:4] A total of 7.9 million people representing more than half of the population of BAY states are in need of humanitarian assistance in 2020.[footnoteRef:5] [2: UNOCHA. Humanitarian Response Plan 2020.] [3: Adamawa, Borno and Yobe States, with 83% of the IDPs located in Borno State.] [4: IOM. Displacement Tracking Matrix. XXIX Report November 2019.] [5: Humanitarian Needs Overview 2020]

Despite difficulties to access many LGAs in Borno state, an intense multi-sector emergency response has been mounted since the beginning of 2016 when newly accessible areas were entered by government and humanitarian partners. The emergency response includes establishment of IDP camps, distribution of food and non-food items, WASH interventions, EPI and Polio and nutrition interventions.

Humanitarian partners have been responding to the protracted emergencies and have scaled-up services to affected populations significantly since the declaration of emergency in 2016. Amongst the programs being implemented are water, sanitation and hygiene (WASH), nutrition and health amongst others. This has necessitated the need to use a data-driven approach in decision making. Thus, the need to implement knowledge, attitude and practice (KAP) study as both a situation analysis tool when developing new interventions as well as outcome evaluation tool.

A KAP study or survey is a representative study of a specific population to collect information on what is known, believed and done in relation to a specific topic — in this case for WASH, nutrition, health and protection issues. KAP surveys can identify knowledge gaps, cultural beliefs, or behavioural patterns that may facilitate understanding and action, as well as pose problems or create barriers for program implementation as well as results. KAP provides fundamental information that can be used to make strategic decisions and is a critical component in the project monitoring and evaluation framework already in place.

Current Status / Available Information

Currently, partners have been implementing stand-alone KAP surveys using differing methodologies and sampling designs. As part of the sector-wide strategy to standardize and harmonize data collection system ensuring synergy and inter-sectoral collaboration, it was agreed that state-wide KAP survey is not out of place. This will standardize the data collection process and harmonize the indicators.

In order to continue to monitor the humanitarian situation and response, a state-wide KAP surveys representative at LGA level is proposed. The survey will use similar methods to ensure comparability and allow partners to monitor health, nutrition, WASH, food security and child protection/gender based violence outcomes.

Objectives

The main objective of the KAP study is to identify knowledge gaps, cultural beliefs, or behavioural patterns that may facilitate understanding and action. They can also assess communication processes and sources that are critical to defining effective activities as well as highlight issues and barriers in programme delivery, and solutions for improving quality and accessibility of services.

· To describe the population’s knowledge, attitude and practice status, with reference to, women and children.

· To develop the data base for Health, WASH, Nutrition and Child protection in NE for reference and for validation of program information

· To facilitate decision making processes for program by Government and Humanitarian partners on how best to meet the needs populations in emergency.

· To understand the KAP during Covid19 to realign the program and strategic directions

Methodology

The survey will utilize a mixed-methods approach[footnoteRef:6]; obtaining both quantitative and qualitative data by utilizing two distinct methodologies of Qualitative Data Collection (qualitative method) and KAP surveys (quantitative methods) to enable us to measure the overall goal of the survey and its specific objectives. [6: Mixed-Methods Approach: is a form of Multi-methodology or multi-method research that is done in a situation when either a qualitative or quantitative approach by itself, is not sufficient to develop multiple perspectives and a complete understanding about a research problem or question, or to sufficiently answer the evaluation question. This involves the mixing of qualitative and quantitative data, methods, and methodologies in a research study. ]

Qualitative Data Collection

The qualitative data collection will utilize Focus Group Discussions (FGD) with beneficiaries and other stakeholders in the community, Semi-Structured Interviews (SSI) with traditional rulers, Community Nutrition Mobilizers (CNM), WASH volunteers and traditional healers, then finally In-Depth Interview (IDI) with hygiene promoters, health care workers, and program staff. Information generated will be used enumerate the likely causes of malnutrition, barriers to child health and the prevailing nutrition and hygiene practices in the project areas. These together with the data from the quantitative techniques to will be utilized to ascertain the efficiency and effectiveness of the current nutrition program. The details of each methodology are as below:

Focus Group Discussions: in this data collection technique, beneficiaries between 8 – 12 will be gathered in the same place and the 2 interviewers (1 facilitator and 1 qualitative note taker) will guide the discussion using the FGD discussion guide to get all the information from the relevant stakeholders in the community on how and why the interventions are working or not. As a rule of thumb, 2 group discussions should be conducted per type of respondent.

Semi-Structured Interviews: where it is not possible to gather 8 – 12 persons or for a category of stakeholders such as traditional rulers, traditional healers and CNM or VCM in the communities visited, a one-on-one SSI will be conducted using the interview guide.

In-Depth Interviews: this will be conducted with stakeholders with in-depth knowledge about the program or intervention to gain the experts view about the program. It is also conducted one-on-one using an interview guide or questionnaire. The targeted stakeholders for this methodology are the HCW and the project/ program staff.

Sampling, Data Collection & Analysis

In qualitative methodology, the sampling, data collection and analysis follow an iterative process that involves collecting data, focusing on the data and analyzing the data continuously (Figure 1) until when no new information is obtained from the field a phenomena refer to as ‘Sampling to Redundancy’ or ‘Sampling to Saturation’. The data obtained is analyzed by focusing on the data after transcribing the interview or discussion notes and or recordings. The data is focused on to remove irrelevant and un-important part of the interview and concentrate on the relevant and important information through coding and identifying themes or concepts within the data with subsequent margin to higher level categories and or theme.

Time

Figure 1. Sequence of qualitative research (Lofland, Lofland, Snow, & Anderson, 2006)

KAP Survey

A KAP survey is a quantitative assessment that use a predefined question formatted in a standardized questionnaire. KAP survey reveal misunderstandings that may represent obstacles to the activities that we would like to implement and potential barriers to behavior change and program improvement. The questionnaire that was used for the baseline estimate will be utilized to allow for comparison between the baseline and the endline surveys.

Study Design

The survey is designed as a cross-sectional household survey using a two-stage cluster sampling representative at LGA level. The survey area consists of 23 accessible LGAs of, Borno state. The 65 LGAs are divided into 10 domains; 2 in Adamawa, 3 in Yobe and 5 in Borno states.

The list of LGAs and estimated populations is as provided in the table below.

Table 1: List of LGAs with Estimated Populations

State

LGA

Population

Borno

Askira/Uba

275,171

Borno

Bama

195,424

Borno

Bayo

167,823

Borno

Biu

326,333

Borno

Chibok

131,734

Borno

Damboa

166,014

Borno

Dikwa

117,618

Borno

Gubio

180,569

Borno

Gwoza

273,202

Borno

Hawul

252,553

Borno

Jere

729,629

Borno

Kaga

125,459

Borno

Kala/Balge

116,985

Borno

Konduga

237,739

Borno

Kwaya Kusar

135,655

Borno

Mafa

117,733

Borno

Magumeri

274,444

Borno

Maiduguri

904,158

Borno

Mobbar

175,015

Borno

Monguno

211,979

Borno

Ngala

130,654

Borno

Nganzai

147,991

Borno

Shani

230,119

The actual representativeness of each of the LGA results will depend on the accessibility of the wards/settlements at the time of the assessment. The aggregated data at state level allows further comparison of results from this result and will be computed using a weighting analysis.

Sample Design

Administratively Nigeria is divided into states and each state is sub-divided into Local Government Areas (LGAs), and each LGA is divided into wards. In addition to these administrative units, during the 2006 population census, each locality was subdivided into census Enumeration Areas (EAs).

The sample was selected using a two-stage cluster design. The clusters for each domain were drawn independently using probability proportional to size (PPS) method. Given recent large-scale population movement, an updated sampling frame was built for Borno. A list of lowest possible unit (villages or camps) available will be used for sampling. Population estimates from the January 2019 polio campaign micro plan as well as VTS population estimates by settlement was used for settlements. Settlements that have less than 20HHs will all be sampled and the remaining HHs supplemented from nearest villages (within 5KM radius of the selected village). Population estimates for internally displaced persons (IDP) camps will be used from the latest International Organization on Migration (IOM) Displacement Tracking Matrix (DTM) report available at the time of the survey (DTM Round XXIX, November 2019).

In-accessible areas will be excluded a priori. Accessibility will be determined by state level security officers and informed by access during the most recent polio campaign.

First stage sampling procedure: cluster selection

The sample will be selected using a two-stage cluster design. The PSU (clusters) will be randomly selected according to the probability proportional to size (PPS) method.

To avoid unforeseen challenges to access the selected clusters during data collection reserve clusters will be selected at this sampling stage using fractional interval systematic sampling[footnoteRef:7]. The reserve clusters will only be used as replacement when original clusters were not reachable during data collection. All reserve clusters will be surveyed if the reserve clusters are needed. [7: on This refers to an equal probability variant of systematic sampling]

Second stage sampling procedure: household selection

The second stage of sampling consists of selecting households within each cluster by using systematic random selection. The team will determine the total number of households in the cluster by completing a household listing of the selected cluster with the support from the community leader. This will serve as the sampling frame for household selection. The households to be sampled are selected using the same fractional interval systematic random sampling.

Segmentation

In a situation where the selected cluster is too large or more than was cluster was selected for a particular settlement or EA, the team under the supervision of a supervisor or coordinator need to divide the cluster and sub-sample a part of it in a process known as ‘Segmentation’. Any cluster that has exceeds 300 households should be segmented.

Sample size determination

The sample sizes for WASH/Child protection at household level were calculated using the sample size estimation for educational assessment as proposed by Krejcie & Morgan (1970)[footnoteRef:8], while the IYCF sample sizes (exclusive breast feeding for children 0-5 months and complementary feeding for children 6-23 months) were calculated using the USAID Feed the Future Population-based Sampling Guide.[footnoteRef:9] These were used as the primary indicators and have been calculated using the following formulas; [8: Krejcie, R.V., & Morgan, D.W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610] [9: Diana Maria Stukel. 2018. Feed the Future Population-Based Survey Sampling Guide. Washington, DC: Food and Nutrition Technical Assistance Project, FHI 360]

For WASH indicators at household levels;

While for IYCF & Health indicators the following formulae was used for individuals;

However, there is a need to convert the number of individuals calculated to number of households required to reach those individuals. Thus, the following formulae was used to do the conversion;

And the result was as presented in the table below:

KAP Survey Protocol, Nigeria 2020

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Table 2 Anthropometry & mortality sample size inputs

LGA

Population

In-Accessible Population

Accessible Population

Average Household Size

EBF Rate (children 0-5 Months)

MDD Rate (children 6-23 Months)

Sample Size

Household

Children 0-5 months

Children 6-23 months

Children

Household

Children

Household

Abadam

42,354

25,039

17,315

 

 

 

 

Guzamala

82,892

76,386

6,506

Kukawa

110,587

52,987

57,600

 

 

 

Mobbar

175,015

118,861

56,154

5.9

46.40%

7.00%

386

79

669

101

285

Nganzai

147,991

57,857

90,134

5.9

46.40%

7.00%

386

79

669

101

285

Askira/Uba

275,171

52,359

222,812

5.7

56.70%

19.30%

386

78

684

240

702

Bayo

167,823

-

167,823

5.7

56.70%

19.30%

386

78

684

240

702

Biu

326,333

12,960

313,373

5.7

56.70%

19.30%

386

78

684

240

702

Chibok

131,734

4,925

126,809

5.7

56.70%

19.30%

386

78

684

240

702

Hawul

252,553

-

252,553

5.7

56.70%

19.30%

386

78

684

240

702

Kwaya Kusar

135,655

-

135,655

5.7

56.70%

19.30%

386

78

684

240

702

Shani

230,119

-

230,119

5.7

56.70%

19.30%

386

78

684

240

702

Bama

195,424

78,023

117,401

5.8

57.00%

19.50%

386

78

672

242

695

Dikwa

117,618

22,308

95,310

5.8

57.00%

19.50%

386

78

672

242

695

Gwoza

273,202

59,274

213,928

5.8

57.00%

19.50%

386

78

672

242

695

Kala/Balge

116,985

7,306

109,679

5.8

57.00%

19.50%

386

78

672

242

695

Ngala

130,654

9,673

120,981

5.8

57.00%

19.50%

386

78

672

242

695

Marte

24,282

9,359

14,923

 

 

 

 

Damboa

166,014

16,941

149,073

5.6

37.50%

4.20%

386

79

705

62

185

Gubio

180,569

143,398

37,171

5.6

37.50%

4.20%

386

79

705

62

185

Kaga

125,459

63,112

62,347

5.6

37.50%

4.20%

386

79

705

62

185

Konduga

237,739

14,101

223,638

5.6

37.50%

4.20%

386

79

705

62

185

Mafa

117,733

17,226

100,507

5.6

37.50%

4.20%

386

79

705

62

185

Magumeri

274,444

114,514

159,930

5.6

37.50%

4.20%

386

79

705

62

185

Monguno

211,979

11,703

200,276

5.6

37.50%

4.20%

386

79

705

62

185

Jere

729,629

3,804

725,825

5.6

45.30%

8.80%

386

79

705

124

369

Maiduguri

904,158

-

904,158

5.6

45.30%

8.80%

386

79

705

124

369

Total

5,884,117

972,116

4,912,001

5.7

45.60%

9.20%

10,422

2,579

16,226

4,161

10,990

The highest sample size for WASH/Child Protection (using 50% prevalence for the worst-case scenario) or for IYCF (using EBF rate and or minimum dietary diversity rate from NE_NFSS round 8 results) is considered for the survey to be able get highest possible precision. Considering the time the team needs for household listing, household selection, interview and travel to the EAs into account, it was determined to complete 20 households or less by a team per cluster per day which resulted in selection the following clusters per LGA (see the table below).

LGA

Households / LGA

Clusters / LGA

Households / Cluster

Mobbar

669

33

20

Nganzai

669

33

20

Askira/Uba

702

35

20

Bayo

702

35

20

Biu

702

35

20

Chibok

702

35

20

Hawul

702

35

20

Kwaya Kusar

702

35

20

Shani

702

35

20

Bama

695

34

20

Dikwa

695

34

20

Gwoza

695

34

20

Kala/Balge

695

34

20

Ngala

695

34

20

Damboa

705

35

20

Gubio

705

35

20

Kaga

705

35

20

Konduga

705

35

20

Mafa

705

35

20

Magumeri

705

35

20

Monguno

705

35

20

Jere

705

35

20

Maiduguri

705

35

20

Total

16,076

796

 

Indicators

The following indicators are proposed to be included in the surveillance program:

1. WASH – collected at household level and are indicators of water quantity, water access, water quality, sanitation and hygiene. The indicators are;

1.1. Average number of litres of potable water per person per day collected per household

1.2. Percentage of households with at least 15 litres per person of protected water storage capacity

1.3. Percent of people who received and shown understanding of improved service quality from solid waste management, drainage, or vector control activities.

1.4. Percent of people targeted by the hygiene promotion program who know at least three (3) of the five (5) critical times to wash hands

1.5. Percent of households targeted by the hygiene promotion program who store their drinking water safely in clean containers

1.6. Percent of people targeted by the hygiene promotion program who report using a latrine the last time they defecated.

1.7. Percentage of households collecting drinking water from protected/treated sources

1.8. Percentage of households with family latrine or toilet

1.9. Percentage of households reporting defecating in a toilet or latrine

1.10. Percent of households in the target population with handwashing facilities that are functional and in use

1.11. Percentage of households practising open defecation

1.12. Percentage of recipient women of reproductive age who are satisfied with their menstrual hygiene management materials and facilities

1.13. Percent of water user committees created and/or trained by the WASH program that are active at least three (3) months after training

1.14. Percent of water points developed, repaired, or rehabilitated that are clean and protected from contamination

2. Nutrition

2.1. Percent of children 0-5months receiving exclusive breastfeeding

2.2. Percent of children 6-23moths receiving 4 or more food groups (MDD)

2.3. Percent of children 6-23months receiving minimum meal frequency

2.4. Percent of children 0-23months receiving appropriate breastfeeding practice

2.4.1. Percent receiving early initiation of breastfeeding within one hour

2.4.2. Percent receiving continuous breastfeeding at 1 year

2.4.3. Percent receiving continuous breastfeeding at 2 years

2.5. Percent of caregivers with understanding of the benefits of breastfeeding

2.5.1. Knowledge of early initiation of breastfeeding

2.5.2. Knowledge of exclusive breast feeding

2.5.3. Knowledge of continuous breastfeeding at 1 year

2.5.4. Knowledge of continuous breastfeeding at 2 years

2.6. Percent of caregivers with knowledge of reasons for diets of young children

2.7. Percent of caregivers with belief in benefits of dietary diversity (perceived benefits)

2.8. Percent of caregivers with preference for targeted foods

2.9. Percent of women of childbearing age (WCBA) receiving 4 or more food groups (WMDD)

2.10. Percent of women of childbearing age (WCBA) receiving iron rich foods

2.11. Percent of children 6-59months receiving vitamin A supplementation (VAS)

2.12. Percent of pregnant women receiving iron folate (FeFo)

2.13. % of Families and mothers to have MUAC for screening of children with SAM

2.14. % of mothers left breast feeding to children below 6 months because of Covid19

2.15. % of mothers and families have stopped feeding children 6-24-month olds

2.16. % of families are able to use the MUAC for screening of children at home

3. Health

3.1. Rate of delivery by skilled birth-attendant

3.2. Rate of ANC visits.

3.3. Health seeking behaviour and walking distance to health facilities

3.4. Knowledge and prevention of common rural communicable disease

3.5. Estimated prevalence of child morbidity (Two-week recall)

4. Child Protection

4.1. % of households reporting children living with people who are not their biological parents of their regular caregivers in their community.

4.2. % of households reporting children without parents living on their own without any parents/adults caregivers in their community

4.3. % of households reporting children neglected and roaming around in the community during school hours

4.4. % of households reporting children hawking or begging on the streets during school hours

4.5. % of households reporting girls are married before the age of 18 years in their community.

4.6. % of households reporting maltreatment of children by their parents or caregivers including beating and other forms of physical abuse in their community.

4.7. % of households reporting neglect and abuse of children because of their disabilities or special needs in their community

4.8. Knowledge and practices on what to do if aware of serious child abuse??

5. Covid-19

5.1. % of households practicing appropriate COVID-19 infection, prevention and control measures

Personnel & Collaboration

1.

2.

3.

4.

5.

6.

6.1. Collaboration

The survey will be implemented in a multi-sectoral and multi-partner approach. The WASH, Nutrition, Health and Child Protection sectors as well as partners will be involved. The implementation approach is such that UNICEF (WASH & Nutrition sections) and Nutrition sector will lead development, planning, training and field data collection not covered by partners. While the partners will lead the implementation in their focus LGAs using the same tools and on the same server managed by UNICEF.

6.2. Recruitment and team organization

The National Bureau of Statistics (NBS) together with National Population Commission (NPopC) and Federal Ministry of Health (FMOH) will identify people to be involved in the survey in areas where UNICEF will implement. While on the other hand, in areas where partners will implement, the selection will vary based on internal processes of partners.

The candidates will be selected based on their experience in surveys and language skills in order to interview the respondents in their native language as much as possible. English language ability is required for all team members.

All enumerators should be a female and should wear culturally appropriate clothes in order not to be refused to undertake the work by the household as men are not allowed to enter household to measure children and women.

Training

The interviewer’s training will last for 3 days in Maiduguri. The training will include the following:

· An overview of the survey and its objectives,

· Interviewing and general communication skills

· Contextualising the questionnaire into the local context

· Systematic random selection of households and segmentation

· Identification of individuals to measure or interview

· How to complete the questionnaires using tablets

· Correct age estimation in months and validation using the calendar of local events

· A pilot test will be conducted before the commencement of data collection. This will be used as an opportunity to assess the tools and evaluate the actual data collection process before deployment of the teams. Feedbacks from the pilot test will be discussed and addressed before actual data collection.

Partners will nominated their staff for the training, who can then cascade the training for their partner specific enumerators.

Fieldwork Plan

The data collection exercise will take approximately 3 weeks. The enumerators for the survey will be assessed during the training and continually throughout the data collection period. Only those teams who are consistently producing high quality data will be retained. If the data quality of a team is found to be unacceptable, their employment will end immediately.

The small number of team per group will allow the supervision teams to provide effective support by reviewing the skills and implementation of all data collection process during entire period.

Detailed fieldwork plan will be created to visit the most remote selected enumeration areas within the state first. This will avoid missing of selected clusters in the area due to inaccessibility from rain or impassable roads.

The team constitutes of experienced and senior staffs from National Bureau of Statistics, National Population Commission and Federal Ministry of Health. UNICEF will provide technical support and supportive supervision throughout the entire process.

Data Collection and Supervision Field Testing of Instrument

The scripted questionnaire will be field tested for validation and calculation of fieldwork duration (duration of questionnaire administration per household and per cluster per day). The field testing will be conducted by a team of enumerators (similar in experience and skills with those that will conduct the field data collection) under the supervision of the survey manager.

Field Data Collection

Samsung Galaxy tab 4 7.0” or Galaxy Tab A6 will be used to collect data in the field. The questionnaires will be developed in ODK and hosted on the ONA (Ona.io). The data will automatically be sent to central server using 3G internet connection. Once, the data was received it will be analysed daily for key quality checks. This will serve as the basis for communication between the coordinator and the rest of the survey teams during entire data collection period.

Prior to the start of the data collection phase of the survey, the selected LGA authorities will be informed about the survey in order to communicate with the community that the data collection will take place in the area. This will help to gain support from the officials and the community during the data collection. Each team has its own vehicle and is accompanied by a driver.

The supervisor is in overall charge of a group. A group consists of 3 teams that cover an average 2 LGAs. He/she is responsible for the daily organization and supervision of the team’s work. He/she assigns work to the team members, responsible for logistic arrangements and where possible also helps the team in locating accommodation. Additionally, he/she is also responsible for checking the quality of the interview by observing the interview and anthropometric measurements.

The Coordinators are responsible to support supervisors to ensure that all necessary arrangements are made before the arrival of the team to states and provide other support based on need. They also support the daily activities of the team based on feedback received from survey manager using data that will be sent to the central server on daily basis. The coordinator in collaboration with the supervisors should identify and support the team that needs more support thereby to improve the overall quality of the survey.

The survey teams will start fieldwork in the same location following training in order to make supervision of all teams by senior survey staff possible during the time that supervision is most needed. To ensure that the travel times from one cluster to the other are minimized as much as possible, the team are also advised to stay in the nearest local government area (LGA).

Data Quality Control and Data Entry Data quality control

To ensure the quality of data, supportive supervision will be provided for the team at different level. The first level of supervision is provided by the team supervisors who are responsible for closely monitoring the work of the teams to ensure that all sampled households are visited, and eligible children and women are included. An important element of this supervision is to periodically return to few selected households and conduct a short re-interview of listing of household members and comparing the list with what was reported originally by the team. The main aim of such re-interviews is to uncover any deliberate distortion of age or omission of household members by interviewers so as to reduce their workload. They will also observe the interview to ensure that the survey team are conducting the interviews as per the interview manual.

The second level of supervision consists of coordinators and state level government officers visit to the field. It is expected that the coordinators and other qualified staffs from state offices will visit teams on regular basis to check on their work. Strengths and weaknesses will be discussed in review session with the teams.

A daily review summarizing key quality issues will be provided to the teams during fieldwork to check the data that was sent using smart phone (tablets). The review will look at issues such as response rates, the age distribution of children, women and household members, the level of missing values for key indicators, time of data collection and quality of anthropometric measurements if any. Any problems that appear from the review will be discussed with the appropriate teams and attempts will be made to ensure that they do not persist.

Data entry

The data will be collected using 3G enabled tablets. Therefore, data collection and data entry will be completed at the same time in the field. This will help to facilitate quick review with the objective to improve the quality of data and real time reporting of the results. In addition to saving the time of data entry it will also help to save money that would have otherwise been spent on second round data entry and validation process.

COVID-19 IPC Measures for Training and Data Collection

1. Enumerators and supervisors will be tested for COVID-19, only negative will be employed/engaged

2. Wearing of masks, individual sanitizers etc

3. Social distancing during data collection, training etc. No hand greetings when visiting household etc

4. FGD and other grouping will adhere to social/physical distancing

5. No sharing of pens etc

6. Vehicles sanitised/decontaminated everyday

7. Approval by SPHCDA

8. Proper training of enumerators on COVID IPC

9. etc

Analysis and Report Writing

The analysis will be completed within a week following completion of data collection. A brief summary report (anthropometry & mortality data only) of the survey will be made available by the end of 2 weeks following completion of data collection. The results will be presented in the standard format. This format includes estimates with 95% confidence intervals.

The report will have estimates for standards indicators. The data quality report will be included in the data quality section of the report. The summary and final report will be made available by the end of August 2020. Stata version 14.0 will be used for analysis of survey data. To account for ongoing, large scale population movement, cluster level weights will be calculated adjusting for selection probability within the cluster and non-response, as described by Brogan et al., 1994.

Dissemination

Dissemination of the survey results to all relevant audience will be conducted both at state and national level. This is to ensure that survey results are used for better programing and to encourage demands for future surveys. The results will be circulated as widely as possible and will also be available for downloading on the National Bureau of Statistics (NBS) and relevant humanitarian website.

Partners will be responsible for their dissemination process as well as audience.

Anticipated limitations and potential biases

13.1. Reliability of the sampling frame

The Master sampling frame used for the random selection of Primary Sampling Units (Enumeration Areas) was built in 2005. As the projections at EA levels are technically difficult to obtain, the choice is made to use the original population estimates for the cluster selection when applying the PPS method. Additionally, in areas with population movement it is expected to have reliable data from states, VTS and DTM report. The reliability of these data can bias the outcome.

13.2. Reliability of the EA maps

The mapping of the enumeration areas dated from 2006 census, which means that the boundaries might have changed since then. Boundaries for PSU in areas with significant population movement will be a big challenge.

13.3. Accessibility

Albeit the road accesses and travel conditions are still acceptable, it is anticipated that, this situation may change due to different reasons.

Annex 1: Implementation timeline

Activities

June 2020

July 2020

August 2020

W1

W2

W3

W4

W1

W2

W3

W4

W1

W2

W3

W4

Planning the survey

 

 

 

 

 

 

 

 

Updating indicators based on previous rounds and current needs

 

 

 

 

 

 

 

 

Engage partners for support

 

 

 

 

 

 

 

 

Review and update survey protocol

 

 

 

 

 

 

 

Planning and budgeting activities

 

 

 

 

 

 

 

 

Organizing logistics

 

 

 

 

 

 

 

 

Sampling and printing of EA maps

 

 

 

 

 

 

 

 

Developing survey tools

 

 

 

 

 

 

 

 

Developing electronic data collection tools

 

 

 

 

 

 

 

 

Programing of tablets

 

 

 

 

 

 

 

 

Pretest the application of tablets/Field testing

Developing training manual

 

 

 

 

 

 

 

 

Training and Implementation

 

 

 

 

 

 

 

 

Recruiting field staffs

 

 

 

 

 

 

 

Training

Field data collection

Data Cleaning, Analysis & Reporting

 

 

 

 

 

 

 

 

Data cleaning and analysis

 

 

 

 

 

 

 

 

Prepare draft summary report

 

 

 

 

 

 

 

 

Share final summary report

 

 

 

 

 

 

 

 

Prepare final report

Dissemination

 

 

 

 

 

 

 

 

ReferencesLofland, J., Lofland, L. H., Snow, D. A., & Anderson, L. (2006). A guide to qualitative observation and analysis (4th Edition ed.). Belmont, CA, USA: Wadsworth Publishing Company,.Brogan D, Flagg EW, Deming M, Waldman R. Increasing the accuracy of the Expanded Programme on Immunization's cluster survey design. Ann Epidemiol. 1994 Jul; 4(4):302-11.