A constant contact community-based epidemiological investigation (C3EI) as part of malaria elimination demonstration project, Mandla district, Madhya Pradesh, India

Abstract

BackgroundIn India, an increase in malaria cases by 21% (223,961 cases) has been reported between 2022 and 2023. Madhya Pradesh ranks 10th in malaria burden, with Mandla district selected for the Malaria Elimination Demonstration Project (MEDP) to demonstrate the feasibility of malaria elimination in a hard-to-reach, tribal-dominated, and hilly forested district. A Constant Contact Community-based Epidemiological Investigation (C3EI) was undertaken by continuous engagement with the community for real-time data collection, mapping of malaria cases, identification of risk factors, and monitoring of intervention outcomes designed to drive effective strategies for malaria elimination.MethodsThe study mapped 1,143,126 individuals from 248,825 households in the year 2017 in Mandla district for constant contact surveillance. Fortnightly household visits were conducted to inquire about febrile episodes, with on-spot diagnosis and treatment. Data collection was done using the SOCH mobile application, and analysis using R.ResultsThe constant contact household surveillance revealed that out of 956,795 individuals, 230,780 (24.12%) unique individuals reported one or more febrile episodes, with a total of 322,577 febrile episodes and 490 malaria episodes (RDT positive). Males had a higher risk of malaria infection than females (OR = 2.62; p < 0.0001). The cumulative incidence of malaria was highest among children aged 5–15 years and pregnant women. Multiple episodes of malaria infections were more common in adults over 30 years. The incidence of malaria per 100,000 persons gradually declined from 26.13 in 2018 to 11.18 in 2020, with the highest incidence during the monsoon season.ConclusionThe C3EI presents a new strategy suitable for disease elimination programmes. Implementing C3EI-type longitudinal studies in elimination projects holds promise for generating data to expedite malaria elimination efforts because the unit of observation is a ‘household’. Such a comprehensive approach allows identification in the gaps in case management for prompt interventions at the household-level.