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Adaptations to SMART surveys in the context of COVID-19 in Cox’s Bazar, Bangladesh

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By Md. Lalan Miah, Bijoy Sarker, Jogie Abucejo Agbogan, Brigitte Tonon, Mary Chelang'at Koech and Md. Shahin Emtazur Rahman

Md. Lalan Miah is the Nutrition Surveillance Manager for Action Against Hunger Bangladesh. He has seven years’ experience leading the nutrition surveillance project in both host communities and refugee camps and leads the Nutrition Sector Assessment and Information Technical Working Group (AIM-TWG).

Bijoy Sarker is a Public Health Nutritionist currently working as SMART Regional Advisor for Asia with Action Against Hunger Canada. He has nearly a decade of emergency nutrition and surveillance experience from Bangladesh, South Sudan and Sierra Leone and as a roving health and nutrition expert for the South Asia region.

Jogie Abucejo Agbogan is the current Nutrition and Health Head of Department for ACF Bangladesh. She has over 12 years’ experience working in nutrition and health in Myanmar, South Sudan, Ethiopia and Bangladesh for ACF and previous experience with other humanitarian agencies in sub-Saharan Africa.

Brigitte Tonon is the ACF France Regional Health and Nutrition Technical Advisor for Asia. She has many years of experience working across multiple countries and HQs for ACF, Première Urgence Internationale and Médecins du Monde in health and nutrition.

Mary Chelang'at Koech is a nutrition and food security officer for the United Nations High Commission for Refugees (UNHCR) Cox’s Bazar sub-office supporting the nutrition and food security programmes. She has worked in nutrition for 12 years across Kenya, Rwanda, Tanzania, Ethiopia and Bangladesh.

Shahin Emtazur Rahman is a Public Health Nutritionist and Senior Nutrition and Food Security Associate for UNHCR. He has nine years’ experience working in nutrition, particularly in refugee camp contexts.

The authors acknowledge the following for their technical and operational support and collaboration: National Nutrition Services (NNS), the Institute of Public Health Nutrition (IPHN), the Ministry of Health and Family Welfare Bangladesh, the Bangladesh Nutrition Sector Assessment and Information Management Technical Working Group and implementing partners. The authors also thank Md. Saiful Islam Talukder and G.M. Mosharaf Hossain and the survey team, the Action Against Hunger Bangladesh Mission, Jana Daher, the Global SMART Initiative and Action Against Hunger Canada.

Funding support was provided by UNHCR, the Bureau of Population, Refugees and Migration, the Directorate-General for European Civil Protection and Humanitarian Aid Operations and the Swedish International Development Cooperation Agency.

Location: Bangladesh

What we know: Nutrition programming, including nutrition surveys, has faced significant disruption as a result of the restrictions in movement arising from the COVID-19 pandemic.

What this article adds: Adaptations to the Standardized Monitoring and Assessment of Relief and Transitions (SMART) survey methodology and operations were made in the context of Cox’s Bazar refugee camps in Bangladesh during 2020 to enable data collection to continue in spite of the risk of COVID-19 transmission. Reduced indicators were collected and the minimum acceptable precision was used to lower the sample size so as to reduce non-essential contact between survey team members and respondents. Prior to the survey, community sensitisation and mobilisation took place to understand the prevailing myths and fears around COVID-19 and garner support for the surveys. Experienced enumerators were selected so that pre-survey training could be shortened and staff were regularly tested throughout training and implementation, personal protective equipment and physical distancing were used by the team members and respondents and anthropometric measurements were taken outside with equipment disinfected between use (and unique mid-upper arm circumference tapes were used by each household). Team members and household members were screened for COVID-19 symptoms regularly and excluded if symptoms were declared. The overall non-respondent rate was very low (5.4%-8.3%) and exclusions due to COVID-19 were low at 1.5%. Adaptations worked to allow the collection of high-quality data. An additional 3 to 5 minutes were required per household to allow for implementation of IPC measures. The experience shows that context-specific adaptations and community sensitisation and mobilisation can enable safe, quality data collection in the COVID-19 context. 

Background

Cox’s Bazar nutrition context

Cox’s Bazar (CXB) is a highly disaster-prone coastal district in Bangladesh and one of 20 of Bangladesh’s 64 districts identified as vulnerable with an estimated poverty prevalence rate of 16.6% (Government of Bangladesh, 2017). The CXB district has a host population of 2,290,000 and an additional estimated population of 871,924 refugees residing in 32 makeshift and two registered refugee camps across Ukhia and Teknaf (sub-districts) (Government of Bangladesh-UNHCR, 2021). Since the influx of refugees in 2017, the Nutrition Sector in CXB has been providing comprehensive nutrition services to address the underlying causes of malnutrition across all camps tar­geting children under five years of age, children over five years of age, adolescent girls and pregnant and lactating women. Although the protracted crisis in CXB has stabilised to some extent, the COVID-19 pandemic has had a significant impact, limiting access to services, which has necessitated adaptations to nutrition programmes. Adaptations to community-based management of acute malnutrition (CMAM) programmes in CXB have been outlined in recent Field Exchange articles.1

Population representative nutrition surveys

Action Against Hunger (ACF) Bangladesh, with the support of ACF France, the ACF Canada SMART team and the ACF UK coverage team, regularly monitor the nutrition and health situations in both refugee camps and host communities. ACF currently leads the implementation of nutrition surveys in CXB and chairs the Nutrition Sector’s Assessment and Information Management Technical Working Group (AIM-TWG). At the national level, ACF is supporting the formation of a National Assessment Technical Working Group. Since 2009, ACF has conducted 85 nutrition surveys in Bangladesh including 60 Standardized Monitoring and Assessment of Relief and Transitions (SMART) surveys, six rapid SMART surveys, six Standardized Expanded Nutrition Surveys (SENS), seven coverage assessments (SQUEAC/SLEAC), three Link Nutrition Causal Analyses (Link NCA) and three health facility assessments. Of these, 54 surveys were conducted in CXB.

SMART surveys by ACF Bangladesh collect data on anthropometry, mortality, morbidity, nutrition supplementation, food assistance, infant and young child feeding practices, food security and livelihoods and Water, sanitation and hygiene (WASH). The data collected informs the formulation of the joint response plan and multi-sector and integrated humanitarian interventions.

Following the release of interim global operational guidance on population level surveys and household level data collection in the COVID-19 context,2 ACF Bangladesh, in consultation with the Nutrition Sector and government authorities, adapted the methodology for conducting SMART surveys and tested this in refugee camps and host communities in CXB between November 2020 and February 2021. The objective of this article is to capture the experiences and key lessons learned while implementing this interim guidance in three refugee camps to support its further development and implementation in other contexts given that most countries globally have to adapt their surveys due to COVID-19.

Adapting surveys in CXB in the COVID-19 context

Necessary technical, operational, logistical and HR adaptations were made in order to minimise the risk of COVID-19 transmission for the targeted surveyed populations and survey teams during the implementation of three SMART surveys. The assessment method was endorsed by the National Nutrition Services (NNS), the Institute of Public Health Nutrition (IPHN) through the CXB District Civil Surgeon’s Office and the Office of the Refugee Relief and Repatriation Commissioner. All adaptations, outlined below, were comprehensively discussed and agreed in a series of meetings, webinars and email exchanges with AIM-TWG, the Nutrition Sector, NNS, the Civil Surgeon’s Office and the global SMART team at ACF Canada and ACF France headquarters.

Methodology adaptations

The number of indicators collected was reduced to include only those critical for programme decision-making including anthropometric data, a few health indicators and mortality data. Indicators related to food security, anaemia and health aspects, which are usually included, were omitted to simplify the approach and limit the interview time in order to reduce the contact time and minimise the risk of COVID-19 transmission.

For sampling, the precision level was kept at the minimum acceptable level as per the SMART guidance3 to limit the sample size thereby reducing further non-essential contacts with the population. A relatively higher non-response rate (NRR) was factored in for refugee populations (Makeshift camp:18%, Nayapara Registered camp:12% and Kutupalong Registered Camp: 18%) compared to similar past surveys to account for the possible refusal and exclusion of households due to COVID-19 related issues.

Operational adaptations

A number of adaptations were made to survey protocols as advised by global guidance, as follows:

Pre-survey training

Survey implementation

In consultation with the AIM-TWG and government officials, additional measures over and above the global guidelines were also put in place to further reduce the risk of COVID-19 transmission for these specific surveys including those conducted in camps. Those additional adaptations were as follows:

Pre-survey preparations

Survey team measures

Table 1: Health screening checklist for survey team

 

Conditions

Morning

(Y/N)

Evening

(Y/N)

Most common and mild symptoms

 

1. Did the staff and/or any team member have a high temperature (≥100.4F/38°C) without a dry cough, tiredness?

 

 

 

2. Did the staff and/or any team member have high a temperature (≥100.4F/38°C) with dry cough, tiredness?

 

 

Mild and less common symptoms (treated from home)

3. Did the staff and/or any team member have a high temperature (≥100.4F/38°C) without a sore throat, diarrhoea, conjunctivitis, headache, loss of taste or smell, aches and pains?

 

 

4. Did the staff and/or any team member have a high temperature (≥100.4F/38°C) with a sore throat, diarrhoea, conjunctivitis, headache, loss of taste or smell, aches and pains?

 

 

Serious symptoms (take immediate medical attention)

5. Did the staff and/or any team member have a running nose, sneezing, shortness of breath, chest pain or pressure, loss of speech or movement?

 

 

Participant screening

A standard health-screening checklist for interviewees was developed jointly in consultation with the Nutrition Sector and AIM-TWG members for the inclusion and exclusion of children and/or households. Body temperature was measured using an infrared digital thermometer and questions were asked as described in Table 2. If any household met any of the four conditions as explained in Table 2, the household was excluded from the survey. If any household had multiple eligible children but at least one child without fever or other COVID-19 signs/symptoms and no other family history of COVID-19 infection, these households were included in the survey. Any other household members with a high fever or other signs or symptoms were asked to isolate from the survey team but this was not considered a household exclusion criteria.

Table 2: Health screening checklist for household inclusion/exclusion

Conditions

Response (Y/N)

  1. Did eligible children (6-59 months) have a high temperature (≥100.4F/38°C) and/or others symptoms of COVID-19 (e.g., dry cough, sneezing, shortness of breath, chest pain or pressure, loss of speech or movement etc.?)

 

 

  1. Did anyone in this household test positive for COVID-19 within the past 14 days?

 

  1. Was anyone in this household in close contact with a confirmed COVID-19 positive patient within at least 14 days?

 

  1. Is anyone in this household currently in home or centre quarantine for isolation?

 

Data collection and supervision

Findings

All three surveys reached the sufficient number of households and children, well above the minimum requirement as per SMART survey guidelines (90% of clusters and 80% of children) to ensure data quality and representativeness (Table 3).  

Table 3: Proportion of households and children included in SMART surveys  

Survey location

Targeted5

households

Households

achieved

 

Targeted

children

Children

 achieved

 

Non-response rate (NRR)

Makeshift camp

611

578 [94.6%]

492

488 [99.2%]

33 [5.4%]

Nayapara registered camp

585

552 [94.4%]

362

305 [84.3%]

33 [5.6%]

Kutupalong registered camp

709

650 [91.7%]

334

346[103.6%]

59 [8.3%]

The overall NRR was very low (5.4 to 8.3%) and much lower than anticipated and used for the sample size calculation (12 to 18%) at the protocol development stage. Table 4 shows the different causes of non-response. This indicates that household exclusion due to COVID-19 exclusion criteria was very low (1.5%) in the Makeshift camp with no exclusions in the other two camps.

Table 4: Distribution of non-response households by cause

Survey area

Absent

     Refused

Excluded due to children’s high fever

Others*

Total non-response rate (NRR)

Makeshift camp

23 [3.8%]

0 [0%]

9 [1.5%]

1 [0.1%]

33[5.4%]

Nayapara registered camp

7 [1.2%]

1 [0.2%]

0 [0%]

25 [4.3%]

33 [5.6%]

Kutupalong registered camp

26 [3.7%]

33 [4.6%]

0 [0%]

0 [0%]

59 [8.3%]

*Wrong address/moved to another place

Although the original plan was to revisit non-response households for inclusion in the survey, this was not required as all three surveys had achieved adequate samples despite the exclusion of some households. The overall data quality for the three surveys was either “good” (Makeshift camp) or “excellent” (the two registered camps) as per the SMART plausibility score. The overall quality of the survey for the Makeshift camp was high but a penalty was given for a standard deviation (SD) of weight-for-height Z-score (WHZ) (SD value <=0.8; acceptable) which was due to higher homogeneity in that camp.

Although there was no standardisation test used, most enumerators were highly experienced and skilled and therefore a high level of standardisation was assumed which resulted in very few outliers in the data.   

The data collection time of 15 minutes for each household, as recommended by the SMART operational guidelines, was not feasible in this context. A minimum of 20 to 25 minutes was required on average per household with the anthropometry and mortality components. Administration of the health screening checklist, measuring of body temperature, asking/putting on masks for household members and disinfecting equipment added to the time required. There was no refusal related to fear of COVID-19 and health and safety measures were well accepted by community members. Almost all households already had facemasks and other PPE that they were willing to use. However, it was often very challenging to maintain a distance of at least one metre especially in the Makeshift camp due to the very limited space available in and around the households.

All survey team members tested negative for COVID-19 prior to the survey and no one developed other signs/symptoms of COVID-19 or became unwell during the survey implementation.

Reflections and key lessons learned

Weighing up the risks and benefits of conducting surveys during the COVID-19 pandemic is important. That was aided in this experience by a thorough series of discussions with Nutrition and Health Sector partners and local health and administration authorities and a constant review of local epidemiological trends around COVID-19. Gaining an understanding of the local context and community perceptions around COVID-19, including stigma, fear and misconceptions, was also important prior to embarking on the survey in this context. This understanding informed community sensitisation prior to the survey and communications during the fieldwork which led to a high level of community compliance with the survey. The selection of locally experienced, skilled enumerators who could understand the context was also important.

There is a high risk that excluding children and households due to high fever will pose a systematic bias by also excluding potentially malnourished children. This could impact the reported malnutrition prevalence and other relevant indicators since there is a general assumption that sick children are more likely to be malnourished. This is unlikely to have affected the results of the three surveys here, given that the exclusion rate was very low, but should be considered as a potential source of bias in SMART surveys in other contexts where COVID-19 rates are higher.

In terms of measures used during the conducting of surveys, several adaptations were made to the interim guidance based on a series of discussions and consultation with the Nutrition Sector, AIM-TWG, NNS, IPHN, the local Civil Surgeon’s Office as well as ACF Canada and France headquarters advisors. Since the COVID-19 crisis was new for everyone and there was a great deal of sensitivity around conducting surveys in this period, a large number of stakeholders were hesitant to embark on the process. A lot of the additional recommendations therefore came from multiple partners, organisations and technical experts which were added to the global guidance particularly for the specific CXB context but which would not necessarily be needed in other settings.

The interim guidelines on SMART surveys recommend the use of both hand gloves and sanitiser for team members. However, using both items proved to be time consuming, resource-heavy and had the potential to create an extra waste management burden at field level. It was therefore decided to only use hand sanitiser (aside from the use of gloves for those cleaning equipment) so as to reduce the resources needed. This appeared to have no negative impact on transmission rates in the context of these three surveys.

Experience from this survey showed that the standard facemask size was difficult to use with children. The recommended 15 minutes allocated for each household was not adequate to complete the anthropometry and mortality components of the survey and apply IPC measures. On the basis of this experience, several recommendations are made to partners who would like to conduct SMART surveys in COVID-19 context, as described in Box 1.

Box 1: Recommendations to implement SMART surveys in the context of COVID-19

Pre-survey preparation

  1. Critically review and monitor the COVID-19 situation in the context before embarking on a decision to conduct a SMART or other population level survey that requires household level data collection.
  2. Inform and consult with local authorities (e.g., local government, law enforcement authorities, camp management committees and the Health and Nutrition Sectors) prior to conducting any survey during the COVID-19 pandemic. This is particularly important during the pandemic as internal and in-country rules and regulations may be imposed including movement restrictions due to the pandemic. Consultation with the relevant authorities is critical to gain the necessary approvals and full cooperation to successfully conduct the survey.
  3. Use local in-country expertise in technical and management survey aspects wherever possible to ensure both quality data collection and the community’s health and safety in the COVID-19 context.
  4. Invest in community mobilisation and advocacy prior to the survey to address rumours and misinformation around COVID-19 in the community.
  5. Adequate funding and time should be planned for the proper adaptation of IPC health guidance, the procurement of necessary disinfectant and PPE items and any unforeseen contingency measures required to make the survey as safe as possible in the COVID-19 context.
  6. Organisations and the Sector/Cluster should focus on the minimum key indicators required in the survey questionnaire to enable sufficient nutrition situation monitoring and evaluation and decision-making in the context. All additional non-essential indicators should not be included in surveys implemented in the COVID-19 context to reduce exposure time to the survey population and households.
  7. Carefully adapt and contextualise the global guidance (e.g., interim global operational guidance on population level surveys and household level data collection in the COVID-19 context) with a group of experts through a technical committee (e.g., AIM-TWG, Sector/Cluster) to ensure that the guidelines suit the unique context in which they are being applied.
  8. The NRR should be carefully estimated during sample size calculations. Child fever prevalence based on a two-week recall period should not be directly used for COVID-19 related NRR for sample size calculations as it may unnecessarily inflate the NNR.

Survey implementation

  1. Review the allocated time per household based on field testing while taking into consideration extra time for health screening and IPC measures during household visits.
  2. Very close monitoring of daily survey field activities by the responsible survey manager is needed to ensure adherence to IPC guidance, data quality, the health and wellbeing of the survey team members and the number of non-responses either due to COVID-19 related rejection or exclusion.
  3. Additional survey days (e.g., two to three days) should be planned for during the COVID-19 pandemic to revisit all missed or excluded households either due to high fever or absenteeism. This will minimise the possible high NRR that may happen if many children and/or mothers/caregivers are found with fever on the designated days of data collection.  

Conclusion

Experience from conducting three SMART surveys in the context of COVID-19 in CXB showed context-specific adaptations can enable the proper application of SMART survey guidelines. In this context, community mobilisation that took into account prevailing community COVID-19 myths and concerns prior to the survey enabled a good response rate and IPC measures prevented virus transmission among respondents and survey team members.  This enabled the collection of information to inform the nutrition response. It is recommended that surveys continue to be conducted despite the extra efforts and resources needed to minimise the risk of virus transmission.

 

For more information, please contact Md. Lalon Miah at surveymgr@bd-actionagainsthunger.org


1 https://www.ennonline.net/fex/63/cmamcxbcovid19adaptations and 
https://www.ennonline.net/fex/63/cxbvitaminasupplementation

2 https://smartmethodology.org/smart-survey-guidance-covid-19/

3 SMART Manual 2.0, 2017 https://smartmethodology.org/survey-planning-tools/smart-methodology/smart-methodology-manual/

4 Family MUAC was already implemented within CXB whereby caregivers are trained to screen their own children for wasting using MUAC tapes with self-referral to nutrition centres if severe or moderate wasting is indicated.

5 The sample size was calculated using ENA for SMART software based on different parameters. A two-stage cluster sampling technique was applied in the Makeshift camp whereas a simple random sampling technique was applied in the two-registered camps.


References

Government of Bangladesh, Ministry of Planning (2017) Preliminary Report on Household Income and Expenditure Survey 2016. Dhaka

Government of Bangladesh and UNHCR (2021) Joint Registration Exercise, 31 January 2021. Accessed at https://data2.unhcr.org/fr/documents/download/85034

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Md. Lalon Miah, Bijoy Sarker, Jogie Abucejo Agbogan, Brigitte Tonon, Mary Chelang'at Koech and Md. Shahin Emtazur Rahman (). Adaptations to SMART surveys in the context of COVID-19 in Cox’s Bazar, Bangladesh. Field Exchange 65, May 2021. p60. www.ennonline.net/fex/65/smartsurveyscovid19coxsbazar

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