Prevalence of afebrile malaria and development of risk-scores for gradation of villages: A study from a hot-spot in Odisha

Abstract

Introduction Malaria is a public health emergency in India and Odisha. The national malaria elimination programme aims to expedite early identification, treatment and follow-up of malaria cases in hot-spots through a robust health system, besides focusing on efficient vector control. This study, a result of mass screening conducted in a hot-spot in Odisha, aimed to assess prevalence, identify and estimate the risks and develop a management tool for malaria elimination. Methods Through a cross-sectional study and using WHO recommended Rapid Diagnostic Test (RDT), 13221 individuals were screened. Information about age, gender, education and health practices were collected along with blood sample (5 μl) for malaria testing. Altitude, forestation, availability of a village health worker and distance from secondary health center were captured using panel technique. A multi-level poisson regression model was used to analyze association between risk factors and prevalence of malaria, and to estimate risk scores. Results The prevalence of malaria was 5.8% and afebrile malaria accounted for 79 percent of all confirmed cases. Higher proportion of Pv infections were afebrile (81%). We found the prevalence to be 1.38 (1.1664–1.6457) times higher in villages where the Accredited Social Health Activist (ASHA) didn’t stay; the risk increased by 1.38 (1.0428–1.8272) and 1.92 (1.4428–2.5764) times in mid- and high-altitude tertiles. With regard to forest coverage, villages falling under mid- and highest-tertiles were 2.01 times (1.6194–2.5129) and 2.03 times (1.5477–2.6809), respectively, more likely affected by malaria. Similarly, villages of mid tertile and lowest tertile of education had 1.73 times (1.3392–2.2586) and 2.50 times (2.009–3.1244) higher prevalence of malaria. Conclusion Presence of ASHA worker in villages, altitude, forestation, and education emerged as principal predictors of malaria infection in the study area. An easy-to-use risk-scoring system for ranking villages based on these risk factors could facilitate resource prioritization for malaria elimination.

Forest malaria: the prevailing obstacle for malaria control and elimination in India

“…31 In Odisha, submicroscopic and asymptomatic infection were reported to be 30% and 79% of the total infections, respectively, in 2019. 32…”

“… 31 In Odisha, submicroscopic and asymptomatic infection were reported to be 30% and 79% of the total infections, respectively, in 2019. 32 Up to 8.4% of the tribal population in Bundwan block in the Purulia district, West Bengal was found to harbour Pf and all the infections were without any clinical manifestation. 33 Genotyping cognate Plasmodium falciparum in human and mosquitoes revealed that asymptomatic infections have more than double the odds of transmission to a mosquito compared with asymptomatic infections.…”

Coverage of community case management for malaria through CHWs: a quantitative assessment using primary household surveys of high-burden areas in Chhattisgarh state of India

“…It can be a key factor in tribal populations and remote geographies in which most of the malaria exists in India and other LMICs. Detection by CHWs has been a big part of the success achieved in malaria-management by another Indian state, Odisha [36,37].…”

Epidemiology of Malaria in East Nusa Tenggara Province in Indonesia: Protocol for a Cross-sectional Study

“…The logistic regression framework will be applied for modelling the unadjusted, adjusted, and final analyses. Once the best model is identified, a malaria risk scoring system will be developed and the allocation of points for each variable will be based on the magnitude of its regression coefficients [ 45 ]. The sum of points for each variable will be used as an approximation to rank the village from the highest to the lowest risk of malaria in the future [ 45 ].…”