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Soil-transmitted helminth surveillance in Benin: A mixed-methods analysis of factors influencing non-participation in longitudinal surveillance activities [1]

['Emma Murphy', 'Department Of Global Health', 'University Of Washington', 'Seattle', 'Washington', 'United States Of America', 'Innocent Comlanvi Togbevi', 'Institut De Recherche Clinique Du Bénin', 'Abomey-Calavi', 'Moudachirou Ibikounlé']

Date: 2023-01 

Abstract Background Despite the significant success of deworming programs in reducing morbidity due to soil-transmitted helminth (STH) infections globally, efforts to achieve elimination of STH as a public health problem or to potentially interrupt transmission will require improving and intensifying surveillance. However, non-participation in surveillance threatens the ability of programs to adequately monitor program status and limited research has been conducted to investigate drivers of non-participation in stool-based surveillance. Methodology/Principal findings This mixed-methods exploratory sequential study took place in Comé, Benin in association with the DeWorm3 Project. Six focus group discussions were conducted with individuals invited to participate in annual DeWorm3 stool surveillance. Thematic analysis was used to identify facilitators and barriers to participation and inform the quantitative analysis. A mixed-effects logistic regression model was built using baseline DeWorm3 survey data to identify factors associated with non-participation. Qualitative and quantitative findings were merged for interpretation. Among the 7,039 individuals invited to participate in baseline stool surveillance, the refusal rate was 8.1%. Qualitative themes included: community members weighing community-level benefits against individual-level risks, circulating rumors about misuse of stool samples, interpersonal communication with field agents, and cultural norms around handling adult feces. The quantitative analysis demonstrated that adults were significantly less likely to provide a stool sample than school-aged children (OR:0.69, 95%CI: 0.55–0.88), a finding that converged with the qualitative results. Individuals from areas in the highest quartile of population density were more likely to refuse to participate (OR:1.71, 95%CI:1.16–2.52). Several variables linked to community-affinity aligned with qualitative results; residing mainly in the community (OR:0.36, 95%CI:0.20–0.66) and having lived in the community for more than 10 years (OR:0.82, 95%CI:0.54–1.25) decreased likelihood of refusal. Conclusions/Significance Optimizing STH surveillance will require that programs reimagine STH surveillance activities to address community concerns and ensure that no subpopulations are inadvertently excluded from surveillance data.

Author summary Soil-transmitted helminths (STH) are a group of intestinal parasites infecting approximately 1.5 billion people globally and resulting in significant adverse health outcomes. STH surveillance is conducted across endemic regions to assess prevalence of infection, to identify areas for mass drug administration implementation, and to monitor progress. The World Health Organization targets the elimination of STH as a public health problem in endemic settings with research currently being conducted to determine the feasibility of interrupting transmission of STH. In order to optimally design and manage programs towards these goals, and to verify whether elimination of STH as a public health problem has occurred, improvements in surveillance are needed. This mixed-methods study took place in Comé, Benin in association with the DeWorm3 Project, to identify drivers of non-participation in stool-based STH surveillance. This study found that certain individuals are more likely to refuse to participate in STH surveillance activities than others, including adults, individuals in urban areas, short-term residents in communities, and those perceiving their families to not be at risk for STH. As STH surveillance is intensified, programs will need to reimagine how surveillance is conducted to address community concerns and ensure that no subpopulations are inadvertently excluded from surveillance data.

Citation: Murphy E, Togbevi IC, Ibikounlé M, Avokpaho EF, Walson JL, Means AR (2023) Soil-transmitted helminth surveillance in Benin: A mixed-methods analysis of factors influencing non-participation in longitudinal surveillance activities. PLoS Negl Trop Dis 17(1): e0010984. https://doi.org/10.1371/journal.pntd.0010984 Editor: Samuel Wanji, University of Buea, CAMEROON Received: August 15, 2022; Accepted: November 25, 2022; Published: January 10, 2023 Copyright: © 2023 Murphy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: Qualitative data cannot be shared publicly because there is a chance responses may be identifiable by location. Anonymous/redacted transcripts are available by request only. Under agreement with the IRBs of the study, data must be blinded until the study concludes. Therefore, to avoid breaching the agreement with the ethical approval bodies, data cannot be shared publicly because the study remains blinded to outcome data. Qualitative and quantitative data are available from the DeWorm3 Institutional Data Access Committee (contact via dw3data@uw.edu) for researchers who meet the criteria for access to these data. Funding: JLW and ARM received the DeWorm3 study funding from The Bill and Melinda Gates Foundation (grant #OPP1129535). https://www.gatesfoundation.org/. ICT, MI, and EFGAA's research is also funded by the DeWorm3 grant as a staff members of the Benin coordinating team. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

Introduction Globally, the World Health Organization (WHO) estimates more than 1.5 billion people are infected with soil-transmitted helminths (STH).[1,2] Individuals with moderate-to-heavy intensity infections experience adverse health outcomes including diarrhea, abdominal pain, anemia, and impaired cognitive and physical development in children [3,4]. These infections occur primarily in low- and middle-income countries across tropical and subtropical regions, and disproportionately affect low-income communities [1,2]. The WHO’s current STH policy is control of STH through mass drug administration (MDA) of albendazole or mebendazole to school-age children and adults in certain high-risk groups (e.g. adolescent girls and pregnant individuals), with the ultimate target of eliminating STH as a public health problem by eliminating morbidity in these groups [1,5–7]. While targeted MDA is successful at controlling morbidity in school-aged children, community transmission continues to occur in many areas with adults serving as reservoirs of infection, particularly of hookworm infections [8–10]. Several studies are underway to determine the feasibility of interrupting transmission of STH via more intensive approaches to deworming, including community-wide MDA (cMDA), which treats all age groups as opposed to just children and specific targeted high risk populations [11–13]. Achieving elimination of STH as a public health problem and/or interruption of disease transmission will require rethinking existing STH surveillance protocols, which are largely underspecified and left to the discretion of endemic countries to design. Community-based surveillance will be necessary for identifying individuals who may have been missed by existing programs and delineating areas with low baseline transmission where cMDA efforts may have a higher probability of interrupting transmission. New surveillance measures will also be essential for confirming elimination of STH as a public health problem or transmission interruption at the level of the implementation unit. Current diagnostics used for STH surveillance require collecting stool samples for microscopy-based assessment of infection, usually via the Kato-Katz technique, though novel approaches including qPCR are also increasingly available [14]. Both methods require collecting fecal samples. Although broad consent and participation in surveillance activities will be necessary for gaining accurate estimates of STH prevalence, minimal research has been conducted to investigate the acceptability of stool-based surveillance and opportunities to optimize participation in surveillance activities. One study in Kenya evaluating factors influencing decisions to participate in treatment and research programs targeting STH and schistosomiasis found associations between socioeconomic status, history of disease, receipt of treatment through the program, and an understanding of the importance of the research with an individual’s willingness to provide samples (urine, blood, and stool) for research purposes [15]. A Ugandan study evaluating the acceptability of sampling procedures (self-collected vaginal swabs, blood draws and stool sample collection) related to the study of human papillomavirus (HPV) vaccine efficacy in the presence of malaria and STH co-infections found that participants had positive views of providing a stool sample but were wary of vaginal swabs and blood sampling due to fears of how the samples might be misused [16]. Evidence from clinical settings in higher income countries indicate that providing stool samples is driven by perceived benefits, clear information about the process, and protocols that assuage fears around hygiene and discretion [17]. Studies of other NTD surveillance activities, including those for onchocerciasis and trachoma, indicate that less invasive sampling procedures are preferable and decisions are similarly driven by perceived benefits, and trust and understanding of the program [18,19]. However the specific factors influencing participation in STH stool-based surveillance activities are not fully understood. High non-participation in STH surveillance activities among some communities may act as a barrier to accurate detection, diagnosis, and elimination of STH. This in turn has implications for identifying geographic areas that are ready for elimination programming, for monitoring program implementation, and for ascertaining elimination status. Understanding drivers of non-participation in STH surveillance activities is essential to identify strategies needed to improve participation in stool sampling. The purpose of this mixed-methods study is to generate evidence regarding the demographic, sociocultural, and financial factors influencing non-participation in STH surveillance activities in Comé, Benin. Findings from this study may have implications for best practices in redesigning STH surveillance should a global policy for STH transmission interruption move forward.

Methods Ethics statement Approval for the informed consent forms and research proposal was obtained from both the Human Subjects Division at the University of Washington (STUDY00000180) and Institut de Recherche Clinique du Bénin (IRCB) through the National Ethics Committee for Health Research (002-2017/CNERS-MS and No: 031-2019/MS/DC/SGM/DFRMT/ CNERS-Ministry of Health, Benin) from the Ministry of Health in Benin prior to this study. All participants provided written informed consent after being provided an explanation of the study in local languages. All data have been de-identified. Furthermore, all researchers involved in this analysis completed human subjects research training per University of Washington requirements. Research Aims This analysis used an exploratory sequential mixed methods design (QUAL ➔ QUANT) to identify factors influencing non-participation in STH surveillance activities. The qualitative analysis aimed to identify perceived facilitators and barriers to providing a stool sample. Findings from qualitative data collection were used to develop quantitative data analysis procedures (model building). The quantitative analysis aimed to explore if the facilitators and barriers identified in the qualitative data held at a population level, in addition to identifying population-level factors driving non-participation in the stool sample surveys. Qualitative and quantitative findings were merged to assess convergence and divergence of qualitative and quantitative results. The DeWorm3 Project This study was nested within the DeWorm3 Project, a cluster randomized control trial based in Benin, India and Malawi that is testing the feasibility of interrupting transmission of STH.[20]. In Benin, the DeWorm3 trial is conducted in the district of Comé, which is located in the Mono Department and has a population size of 94,969 persons, per baseline study estimates. The trial site is divided into forty clusters, randomized to receive either annual MDA of albendazole to school-aged children (standard of care) or biannual cMDA of albendazole to all eligible age groups. Treatment was provided for three years (June 2018-December 2020) followed by two years of surveillance to monitor for recrudescence (2021–2022). More information about the DeWorm3 study design can be found elsewhere [11]. As part of DeWorm3 surveillance activities to monitor changes in STH prevalence and infection intensity over time, 150 individuals from each cluster were invited to participate in a longitudinal monitoring cohort (LMC). LMC participants were randomly selected at baseline from an age-stratified census (30 pre-school-age children, 30 school-age children, 90 adults) of current cluster residents [21]. LMC participants provided annual stool samples throughout the study period to assess changes in STH prevalence and rates of reinfection. Participants in control clusters (who are not routinely offered treatment via the DeWorm3 Project) who were found to have moderate-to-heavy intensity of STH infections via Kato-Katz were followed-up with and offered deworming treatment. This analysis uses data from the baseline LMC in Benin, with consenting procedures and sampling occurring March-May 2018. Qualitative methods Six focus group discussion (FGDs) were conducted with individuals invited to participate in the first LMC to understand factors influencing their decision to provide a stool sample for surveillance in December 2019. Purposive sampling was used to sample individuals from DeWorm3 clusters with high refusal rates (>7.5% refusal) and low refusal rates (<4.5% refusal). Sampling lists of refusals and non-refusals were generated for the selected clusters and the study team contacted those individuals via phone and/or household visit. Three FGDs were conducted in each setting (high refusal and low refusal clusters). Both adults invited to participate in the LMC and adult parents or guardians of children invited to participate in the LMC were sampled. For each FGD, quota sampling was used to ensure participants included a balance of both people who provided a stool sample during the LMC and people who refused, either at the time of recruitment or the time of sample collection. FGD respondents in high refusal clusters were sampled from five different study clusters. FGD respondents in low refusal clusters were sampled from sixteen clusters in order to identify enough people who refused to provide a stool sample in these settings. Adult FGDs were divided by gender to create a more comfortable atmosphere for participants to discuss their personal experiences with stool sampling. FGDs with parents/guardians were not divided by gender. Twenty individuals were sampled for each FGD. Many invited participants were unwilling or unable to participate in the scheduled discussion, resulting in FGDs consisting of 5–8 participants. Of the FGD participants, 2–4 in each group refused to provide a stool sample. Table 1 presents a summary of the sample and sampling frame. PPT PowerPoint slide

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TIFF original image Download: Table 1. Sampling frame. https://doi.org/10.1371/journal.pntd.0010984.t001 FGDs were conducted using a semi-structured question guide informed by the Theory of Planned Behavior (TPB), which has been used previously for similar research questions [17,22]. Fig 1 presents the TPB as applied to this study. The question guide (S1 Appendix) was piloted by the Benin research team outside of the selected study areas and adapted thereafter. All FGDs were led by members of the Benin research team trained in FGD facilitation and conducted in the local language (Pédah or Mina) or in French. All the FGDs were audio-recorded following written consent from participants. Audio data from the FGDs were transcribed into French and underwent quality control checks by the Benin research team to ensure cultural nuances were maintained in the French translation. The French transcripts were then translated into English by a research team member outside Benin. Afterwards, a final round of quality control checks on the French-to-English translation were conducted. PPT PowerPoint slide

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TIFF original image Download: Fig 1. Theory of planned behavior conceptual framework applied to STH surveillance participation. https://doi.org/10.1371/journal.pntd.0010984.g001 English FGD transcripts were coded using the qualitative analysis software ATLAS.ti 9. A preliminary codebook was developed in advance, informed by the TPB. A mixture of deductive and inductive coding techniques was used to allow for iterative adaptations to the codebook. See S2 Appendix for codebook. Each transcript was coded initially by a primary coder (EM) and validated by a secondary coder (ICT) who reviewed all coding decisions, added new codes, or removed codes. A standardized validation tracker was used to record instances of disagreement and a third researcher (ARM) served as a tiebreaker as necessary. The coding team met frequently to reflect on their unique positionalities in relation to the study population; the understanding of local culture provided by the coder based in Benin (ICT) was influential in defining the final themes. Thematic saturation in coding was reached when no new emerging codes or themes were identified across coders. Once all FGD transcripts were coded, case memos summarizing emerging themes and noting exemplary quotes were developed jointly by the two coders for each setting (high and low refusal clusters) to identify salient themes. Quantitative methods This analysis included 7039 individuals invited to participate in the baseline LMC survey in Benin. Twenty-two observations (0.31%) were excluded from the analysis due to incomplete data for the outcome of interest (n = 16) or the population density variable (n = 6). These 7039 individuals represented 5821 households as multiple individuals could be sampled from the same household. Demographic information was ascertained during a baseline census of all households in the study catchment area and/or via a baseline survey administered during the first LMC survey. Individuals that consented to participate in the LMC were asked to provide a fecal sample at the time of the baseline survey. We conducted an exploratory analysis to identify the prevalence and factors associated with non-participation in the baseline LMC in Benin. The primary outcome of interest was a binary participation variable. Non-participation indicates if the individual either: a) did not consent to provide a stool sample, or b) consented but did not provide a sample at the time of collection. We present descriptive statistics (proportions, means, and standard deviations) of sampled individuals who did and did not refuse to provide a sample, separately by age, sex, SES, religion, language, education, household toilet type, time in current residence, place of main residence, population density, village population size, and baseline cluster STH prevalence. The SES variable is an asset-based index compiled using principal component analysis, following the procedure described in the Demographics and Health Survey [23,24]. Either a Pearson’s Chi-squared test or a Welch Two Sample t-test was used to test the associations between dependent and independent variables. We conducted backwards stepwise model building to identify factors associated with non-participation in baseline stool sampling. The choice of independent variables considered for inclusion in the analysis were based on available data, existing literature, and a hypothesis-driven conceptual framework driven by the qualitative thematic analysis (S1 Fig). We then developed a mixed-effects logistic regression model using all non-collinear variables of interest [25]. Collinearity of variables was assessed using a mixture of Pearson’s correlation coefficients (0.8 cut-off), chi-square tests, and knowledge of data architecture, as appropriate. The full model was then simplified using backward stepwise elimination. We compared the Akaike information criterion (AIC) of the full model to the AIC of models in which each variable, separately, was dropped [26]. The model was adjusted for Cluster ID during each step. The reduced model with the lowest AIC was kept and the process was repeated until AIC was no longer further reduced in the adjusted model. Adjustments for multiple comparisons were made by controlling the false discovery rate [27]. We present results from the fully adjusted model: odds ratios, 95% confidence intervals and the adjusted p-value. All statistical analyses were conducted using R and RStudio software (version 4.1.2) [26].

Discussion STH surveillance programs must achieve both high coverage and representative sampling in order to optimally measure progress. However, surveillance can be limited by both low levels of participation and systematic non-compliance. Among the DeWorm3 trial sites, baseline refusals rates among individuals asked to provide a stool sample ranged from approximately 8% (Benin and India) to 38% (Malawi). Notably, these refusals were observed in a trial setting, suggesting refusals could be even higher in routine public health surveillance programs. Despite this, there is limited evidence in the published literature regarding the acceptability of stool-based surveillance, and factors that influence participation. Motivated by observed refusals to consent to STH surveillance activities associated with the DeWorm3 trial in Comé, Benin, this study aimed to understand determinants of these refusals. This paper presents a mixed-methods analysis of factors influencing non-participation in stool sample-based STH surveillance programs. This study identified several individual-level characteristics that influenced non-participation in STH surveillance surveys. Both qualitative and quantitative data demonstrated adults are less willing to provide their stool sample in comparison to providing a stool sample from their child (Table 4). Adult refusals were more frequent than the refusal to provide consent for a child to provide a sample. Systematic reviews examining factors affecting participation in MDA programs for schistosomiasis and lymphatic filariasis, similarly found that adults were less likely to participate, as compared to children [29,30]. Given that adults can serve as reservoirs of infection for STH in many communities, systematic non-participation of adults in STH stool surveillance may pose a challenge to accurately estimating STH prevalence within elimination programs. PPT PowerPoint slide

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TIFF original image Download: Table 4. Points of convergence / divergence between qualitative and quantitative findings. https://doi.org/10.1371/journal.pntd.0010984.t004 Secondly, individuals from Pédah-speaking households were less likely to refuse to provide a stool sample than other language groups. In the Beninese context, language group largely aligns with ethnicity which also drives cultural habits and norms. Furthermore, in Comé, the Pédah communities more commonly live in rural areas, in comparison to Mina and Watchi-speaking families that are concentrated in urban or peri-urban areas. Thus, language may serve as a proxy for urbanicity. This trend aligns with other quantitative findings about population density, where increased density was linked with increased refusals. Other studies exploring perspectives of MDA for both STH and schistosomiasis found that perceptions of infection risk increased participation in MDA [29,31]. In urban settings, where sanitation infrastructure tends to be more advanced and healthcare access more readily available, individuals may perceive themselves to be at lower risk of STH, and thus are more likely to refuse to participate in stool surveillance. Qualitative data from this study similarly linked experiences with STH symptoms and perception of it being a problem in the community with increased participation, supporting this hypothesis. Another explanation for why increased population density was associated with increasing refusals to provide a sample could be due to the ease with which rumors about misuse of stool samples and misinformation about the potential dangers of providing a sample can circulate in communities with high population density. These differences in participation are particularly concerning as rural-to-urban migration increases; if urban populations are more likely to refuse consent for STH surveillance, programs will need to address this. An important driver of participation in stool-based surveillance identified by this study is recognition of benefits for the collective community. FGD respondents who provided a stool sample reported prioritizing community-level benefits (e.g. that surveillance will help inform treatment programs and reduce STH prevalence in the community) and that these benefits outweighed individual aversion to handling feces and other perceived individual-level risks. In contrast, refusal to provide a sample was largely driven by mistrust of the sample’s purpose and fear about misuse or physical harm to the individual. These results parallel findings from other settings that tie decisions to participate in STH programs, willingness to provide a stool sample for diagnostic purposes, and consent to NTD surveillance activities to an understanding of the importance of the research, fears of how the samples might be misused, and perceived benefits [15–17,19]. Similarly, studies examining participation in MDA have found that trust in the program, rumors about harmful consequences, and perceptions of benefits drive acceptability of treatment [29–32]. Of note, findings from this study align with evidence from high-income settings where patients faced barriers to providing a stool sample in a primary healthcare setting due to a lack of information and concerns about privacy [17]. That individuals are acting on their belief of the intervention’s benefit for the community is linked with quantitative findings that suggest an influence of community cohesion/identity on participation. Individuals who resided in the community at least eleven years were less likely to refuse to provide a sample, suggesting the importance of community identity for participation in public health surveillance. Similarly, individuals who did not reside in the community for the majority of days in the six months preceding the survey were substantially more likely to refuse to participate. Interventions targeting improved community building may be important for increasing participation in public health surveillance activities that primarily afford community benefit. Table 4 presents a full matrix of points of convergence (and divergence) between the qualitative and quantitative findings. Several concrete recommendations for STH surveillance programs were generated from this work. If STH surveillance is intensified to achieve and document progress towards elimination as a public health problem and/or transmission interruption, programs will need to understand who is not participating in each setting. Programs will need to disaggregate refusal data based on key demographics to understand if certain populations are refusing to provide a sample at higher rates. In addition to understanding who is refusing to participate in STH surveillance, programs will need to better understand why those individuals or groups are hesitant. Investing in learning about community perspectives, priorities, and beliefs about public health surveillance will be key to ensuring the program’s success. Ideally such research should be conducted in advance of large surveillance campaigns to increase acceptability. These findings also suggest programs should focus on addressing misinformation and demonstrating the benefits of stool surveillance for a community, even where perceived risk of STH is low. This will have implications for community engagement strategies, training for sample collectors, and communication messages. Programs thus have an opportunity to reimagine how STH surveillance is conducted to address community concerns and ensure groups are equally represented in surveillance data. Limitations This study has several limitations. First, a high proportion (70%) of individuals sampled for the FGD were unreachable, unwilling, or unable to participate. This sampling frame may skew findings, especially if individuals not included in the FGD were also more likely to refuse to participate in the study. Secondly, due to limitations in time and budget, this study was unable to conduct a member checking exercise, wherein main findings are shared with FGD participants for feedback and confirmation. However, the research team in Benin drew from their field experience and cultural knowledge to validate the themes emerging from the qualitative analysis to address this limitation. FGDs may also inadvertently introduce social desirability bias due to the group format of data collection. Quantitative data collection tools were developed prior to the qualitative analysis; thus, there may be some drivers of participation identified in the qualitative data that were not explored quantitatively, such as previous experience providing a stool sample. In the quantitative analysis, the proxy measures for community solidarity may be imperfect measures. Further studies are warranted to identify strong indicators of community solidarity. Additionally, while the choices made for this analysis are appropriate for exploratory research questions, it should be noted that using stepwise regression to build the quantitative model and interpretating results from a multivariate analysis have their limitations [33,34]. This analysis drew on data only from the Comé district in Benin. Some findings, particularly those pertaining to local cultural customs or beliefs, may not be generalizable to other settings.

Conclusion This study found that certain groups of individuals are more likely to refuse to participate in STH surveillance activities than others. Our findings suggest that adults, persons who do not reside full time in the community, newly arrived members to the community, individuals who do not perceive themselves or their communities to be at risk for STH, and individuals exposed to convincing misinformation are more likely to refuse to provide a stool sample. STH surveillance must achieve high levels of representative participation; otherwise, programs could misidentify priority areas for implementation or bias verification data. This is of particular concern if groups refusing to participate in surveillance also refuse to participate in deworming campaigns.

Acknowledgments The authors wish to thank all of the study participants, communities, community leaders, national NTD program staff, and local, regional, and national partners (Programme National de lutte contre les Maladies Transmissibles du Ministère de la Santé du Bénin) who have participated in or supported the implementation of the DeWorm3 study. We thank and acknowledge the entire DeWorm3 team in Benin for their work in data collection and study implementation. We also thank and recognize Sean Galagan, Kristjana Asbjörnsdóttir, Emily Pearman, and Ken Tapia for providing consultations on data and quantitative data analysis. Mitsuko Hasegawa supported the development of the initial project design and qualitative data procedures. Additional consultation was sought from the Center for Studies in Demography & Ecology at the University of Washington (Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant, P2C HD042828).

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