BMC RESEARCH (OPEN ACCESS)

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Rijal et al. Tropical Medicine and Health (2019) 47:21 https://doi.org/10.1186/s41182-019-0148-7

Micro-stratification of malaria risk in Nepal: implications for malaria control and elimination

Komal Raj Rijal¹, Bipin Adhikari², Nabaraj Adhikari¹, Shyam Prakash Dumre³, Mayur Sharma Banjara⁴, Upendra Thapa Shrestha¹, Megha Raj Banjara¹, Nihal Singh⁵, Leonard Ortegea⁶, Bibek Kumar Lal⁷, Garib Das Thakur⁷ and Prakash Ghimire^1,5*

* Correspondence: prakashghimire@gmail.com

¹Central Department of Microbiology, Tribhuvan University, Kirtipur, Kathmandu, Nepal

²Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.

³Department of Immunogenetics, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Nagasaki, Japan.

⁴World Health and Research Centre, Kathmandu, Nepal.

⁵World Health Organization (WHO), Country Office, Kathmandu, Nepal

⁶Global Malaria Program, World Health Organization Headquarters, Geneva, Switzerland.

⁷Epidemiology and Disease Control Division (EDCD), Department of Health Services, Ministry of Health and Population, Kathmandu, Nepal.

ABSTRACT

Background: A significant reduction in malaria cases over the recent years in Nepal has encouraged the government to adopt a goal of “malaria-free nation by 2025.” Nevertheless, to achieve this goal, it is critical to identify the epidemiological burden of malaria by specific regions and areas for an effective targeted intervention. The main objective of this study was to estimate the risk of malaria at Village Development Committee (VDC) level in Nepal based on disease, vector, parasite, and geography.

Methods: In 2012, the micro-stratification of malaria risk was carried out in 75 districts of Nepal. Instruments such as a questionnaire, case record forms, and guidelines for malaria micro-stratification were developed and pre-tested for necessary adaptations. Village Development Committee (VDC)-wise malaria data were analyzed using exploratory statistics and were stratified by geographical variables that contributed to the risk of malaria. To understand the transmission risk at VDC level, overlay analysis was done using ArcGIS 10. To ensure transparent, reproducible, and comprehensible risk assessment, standard scoring method was selected and utilized for data from 2009 to 2011. Thus identified, three major variables (key determinants) were given weights (wt.) accordingly to stratification of the malaria risk (disease burden, “0.3” wt.; ecology/vector transmission, “0.5” wt.; and vulnerability-population movement, “0.2” wt.).

Malaria risk in a VDC was determined based on the overall scores and classified into four categories: no risk, low risk, moderate risk, and high risk.

Results: Analyzing the overall risk based on scoring of the total VDCs (n = 3976), 54 (1.36%), 201 (5.06%), 999 (25.13%), and 2718 (68.36%) were identified as high-, moderate-, low-, and no-risk categories for malaria, respectively. Based on the population statistics, 3.62%, 9.79%, 34.52%, and 52.05% of the country’s total population live in high-risk, moderate risk, low-risk, and no-risk VDCs for malaria, respectively. Our micro-stratification study estimates are 100,000 population

at high risk. Regional distribution showed that the majority of the high-risk VDCs were identified in the Far- and Midwestern regions (19 and 18 VDCs) followed by Central and Western regions (10 and 7 VDCs) with no high-risk VDCs in the Eastern region. Similarly, 77, 59, 27, 24, and 14 VDCs of the Central, Mid-western, Western, Eastern, and Far-western regions, respectively, were found under moderate malaria risk. Of the low-risk VDCs, 353, 215, 191, 148, and 92 were respectively from the Central, Eastern, Western, Far-western, and Mid-western regions.

Conclusions: The current micro-stratification study provides insights on malaria risk up to the VDC level. This will help the malaria elimination program to target interventions at the local level thereby ensuring the best utilization of available resources to substantially narrowed-down target areas. With further updates and refinement, the microstratification approach can be employed to identify the risk areas up to smaller units within the VDCs (ward and villages).

Keywords: Malaria, Micro-stratification, Elimination, Intervention, Nepal