Reaching the last mile towards malaria elimination in Chhattisgarh, India.

Authors

Diamond Prakash Sinha, B M Shrinivasa, M Avinash, J Harshitha, Juhi Tiwary, Kajal Bankoti, Gunjan Negi, Viprasha Tomer, Jitendra Kumar, Vani H Chalageri

Published in

Journal of vector borne diseases. Oct 21, 2026. Epub Oct 21, 2026.

Abstract

While malaria incidence has decreased across India, Chhattisgarh continues to harbour a major proportion of national caseloads. Within the 11-state Global Fund evaluation framework (37,976 households), this study evaluated community intervention utilization, care-seeking timelines, topographic road tortuosity, and spatial clustering in southern Chhattisgarh to guide last-mile elimination.
A multi-stage cross-sectional cluster survey evaluated 4,041 households (18,184 individuals) across 40 primary sampling units in five high-endemic districts (Bastar, Bijapur, Dantewada, Narayanpur, Sukma) during peak transmission. Spatial autocorrelation (Global Moran's I , LISA) and multivariable Generalized Estimating Equations (GEE) identified determinants of prompt care seeking, febrile morbidity, and confirmed malaria, incorporating geodesic distances and road tortuosity.
Net ownership covered 93.3% (92.4% state-procured, 81.5% intact), sleeping compliance exceeded 97% in vulnerable groups, and 99.1% sought care at public facilities. Diagnostic blood testing reached 99.2% of febrile patients, with village Mitanins (ASHA workers) performing 60.4% of tests. Spatial clustering was confirmed (Moran's I = 0.539, p = 0.001), with 5 Low-Low cold spots in Bastar demonstrating transmission interruption feasibility. Conversely, IRS acceptance was 30.1%, and 28.8% of confirmed cases ceased radical cure prematurely due to symptom resolution (65.8%). Below Poverty Line status reduced prompt care seeking (< 24 hours) by 66% ( AOR = 0.34, p = 0.043), and road tortuosity averaged 1.44 (peaking at 2.78 in Dantewada).
High commodity coverage coexists with care-seeking friction, premature treatment cessation, and focal clustering. Achieving elimination requires micro-stratified hotspot targeting, Mitanin-supervised directly observed therapy, terrain-calibrated mobile outreach, and wage-loss compensation.

PMID:
42904874
Bibliographic data and abstract were imported from PubMed on 23 Oct 2026.

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