Optimizing community health workers and nonbiomedical approaches to assess the burden of soil-transmitted helminthiasis in a school-aged population in rural Rwanda.
Background
Soil-transmitted helminths (STHs) remain a public health problem for children in low- and middle-income countries. Conventional methods for STH diagnosis require well-equipped laboratories and trained personnel, which are often scarce or inaccessible in rural and resource-limited settings. Algorithmic non-biomedical screening tools are a potential strategy for community health workers (CHWs) to ensure rapid STH detection and referral of children. This exploratory feasibility study aimed at assessing whether a CHW-led, algorithm-based screening program could identify school-aged children with symptoms suggestive of STH and examining behavioral and environmental factors associated with a positive screening outcome in rural Rwanda.
Methods
We conducted a cross-sectional feasibility study of 746 school-aged children in Musanze District, Rwanda, between August 2021 and November 2022. CHWs, trained as School-Based Health Agents, used the Beta CommScreen, an algorithmic nonbiomedical screening tool based on WHO-defined symptomatology and water, sanitation, and hygiene (WASH) indicators, to assess the risk of STH infection. CHWs engaged teachers and community members in developing a bundle of interventions, such as deworming campaigns, WASH education, and targeted home visits. Multivariate logistic regression (Stata 15.1) was used to identify factors associated with presumptive STH infection.
Results
Among the 746 children screened, 322 (43%) reported symptoms consistent with possible STH infections, 220 (29%) were referred to the clinic for treatment, and the remaining children (102, 14%) were provided with deworming medication at school. Having a CHW for routine monitoring and not walking barefoot were associated with a lower risk of STH symptoms (OR = 0.36, 95% CI: 0.21, 0.64) and (OR = 0.49, 95% CI: 0.08, 3.11), respectively. While handwashing behaviors were significant in bivariate analyses, they did not retain statistical significance in the multivariate model. Other factors, including place of residence and age, were also not associated with STH symptoms.
Conclusions
The findings indicate that CHWs can effectively utilize a simplified algorithmic screening tool to identify children with symptoms suggestive of STH infections. This CHW-led model, when integrated within existing health and education systems, may enhance early detection and referral pathways. Further studies are needed to validate the screening tool, assess its diagnostic accuracy, and evaluate the cost-effectiveness and scalability of this approach.