Spatiotemporal distribution of malaria prevalence in the district Anuppur, central India

Manish Kumar Dwivedi, Sanjeev Bakshi, Shruti Sonter, Shringika Mishra, Prashant Kumar Singh


Background: In the current study, 2013±16 medical data were examined to evaluate intervention effects on malaria prevalence in central India. Spatiotemporal variation in the distribution of malaria types (PV, PF, and PV-PF) was also investigated and geographical distribution of malaria prevalence in central India first time.

Methods: The data was collected from the primary health centers, sub health centers, community health centers, and district hospital. The data was used for the calculation of annual blood examination rate, annual parasite incidence, blood slide positive rate, blood slide falciparum rate, % PF, % PV, and % PV-PF types of malaria. The rate of malaria was transformed ( ) for carrying out statistical analyses. ANOVA models were considered for analysis of the data. The minimum deviation informatics statistic has been used to compare the spatiotemporal distribution of malaria types. The spatiotemporal distribution maps of malaria prevalence and mosquito breeding sites were generated using the geographic component software ArcGIS 10.3.

Results: The results display that space was an important significant factor for malaria prevalence. Kotma, one of the blocks of the study region displayed varying geographic patterns of dominance. The analysis for the presence of malaria types indicated that space was an important source of variation for the rate of malaria due to Plasmodium falciparum. The distributional patterns of the malaria types, as observed in the empirical data were tested using the MDIS statistic and findings indicate that the distributions of malaria types for the spatial points, namely Pushparajgarh, Kotma, and Anuppur were not the same over the selected time points. The geographical maps mainly displayed the active mosquito breeding sites in river areas and handpump areas namely Karpa, Laidara, Khamraudh, Rajendragram, Sivarichndas, Basaniha, Soniyamar, Kiragi. The maps also displayed 46% high risk, 34% moderate risk, and 20% low-risk area.

Conclusions: The prevalence of malaria in this tribal-dominated area shows that was governed by mosquitogenic factors and their transmission.


ANOVA, Malaria incidence, Malaria prevalence, Minimum deviation informatics statistic, Spatiotemporal

Full Text:



Epidi TT, Nwani CD, Ugorji NP. Prevalence of malaria in blood donors in Abakaliki Metropolis, Nigeria. Sci Res Essay. 2008;3:162-4.

Mccutchan TF, Piper RC, Makler MT. Use of malaria rapid diagnostic test to identify Plasmodium knowlesi infection. Emerg Infect Dis. 2008;4:11-3.

Sharma RS, Sharma GK, Dhillon GPS. Intervention measures for transmission control; in epidemiology and control of malaria in India, New Delhi. Nat Malar Erad Program. 1996;218-24.

Sharma VP. Current scenario of malaria in India. Parassitologia. 1999;41:349-53.

NMEP. Annual Report-1991. National Malaria Eradication Programme-India, Delhi; 1992.

Dash AP, Valecha N, Anvikar AR, Kumar A. Malaria in India: Challenges and opportunities. J Biosci. 2008;33:583-92.

WHO. World Malaria Report. WHO. 2020. Available from: i/item/9789240015791. Accessed on 3 December 2020.

WHO. World Malaria Report. WHO. 2019. Available from: i/item/9789241565721. Accessed on 3 December 2020.

Singh N, Dash AP, Thimasarn K. Fighting malaria in Madhya Pradesh (Central India): Are we loosing the battle? Malar J. 2009;8:1-8.

Singh N, Dash AP, Varun BM, Kataria OM. Tribal Malaria. ICMR Bull. 2004;34:1-10.

Pattanayak S, Sharma VP, Kalra NL, Orlov VS, Sharma RS. Malaria paradigms in India and control strategies. Indian J Malariol. 1994;31:141-99.

Sarbib JL, Nankani G, Patel P. The booster program for malaria control: putting knowledge and money to work. Lancet. 2006;368:253-7.

Dhingra N, Joshi RD, Dhillon GPS, Lal S. Enhanced Malaria Control Project for World Bank support under National Malaria Eradication Programme (NMEP). J Commun Dis. 1997;29:201-8.

Barat LM. Four malaria success stories: How malaria burden was successfully reduced in Brazil, Eritrea, India, and Vietnam. Am J Trop Med Hyg. 2006;74:12-6.

The Statistics Portal India. 2017. Available at: Accessed on 3 December 2020.

Mavalankar D. Doctors for tribal areas: issues and solutions. Indian J Community Med. 2016;41:172-6.

Singh N, Singh MP, Saxena A, Sharma VP, Kalra NL. Knowledge, attitude, beliefs and practices (KABP) study related to malaria and intervention strategies in ethnic tribals of Mandla (Madhya Pradesh). Curr Sci. 1998;75:1386-90.

Gohel A, Makwana N, Rathod M, Sarkar A, Dipesh, P. Problems faced by ASHA workers for malarial services under NVBDCP: a cross sectional study. Int J Res Med Sci. 2015;3:3510-3.

Shirayama Y, Phompida S, Shibuya K. Geographic information system (GIS) maps and malaria control monitoring: intervention coverage and health outcome in distal villages of Khammouane province, Laos. Malar J. 2009;8:217.

Laurini R. Information systems for urban planning: a hypermedia cooperative approach, CRC Press: Boca Raton, FL, USA; 2014:368.

Census 2011. Anuppur District Population, Caste RD Madhya P. Census 2011. Available from: Accessed on 3 June 2021.

Chandramouli C. Anuppur District census handbook village and town directory. Directorate of census operations Madhya Pradesh. Census of India 2011, Madhya Pradesh, series -24, part XII-A. 378. 2015.

Mushinzimana EM, Stephen M, Noboru L, Li F, Chen-Chieng B, Ling K, et al. Landscape determinants and remote sensing of Anopheline mosquito larval habitats in the western Kenya highlands. Malar J. 2006;5:13.

Kullback S. Information Theory. John Wiley Sons; 1959.

Koh HK, Jacobson M. Fostering public health leadership. J Public Health. 2009;31:199‑201.

Begun JW, Malcolm JK. Leading public health: a competency framework. New York: Springer Publications; 2014:290.

Dikid T, Jain SK, Sharma A, Kumar A, Narain JP. Emerging and re-emerging infections in India: an overview. Indian J Med Res. 2013;138:19-31.

Nath DC, Mwchahary DD. Malaria prevalence in forest and nonforest areas of Kokrajhar District of Assam. Int Sch Res Netw Public Health. 2012;9.

Singh MP, Saha KB, Chand SK, Anvikar A. Factors associated with treatment seeking for malaria in Madhya Pradesh, India. Trop Med Int Health. 2017;22:1377-84.

Rougeron V, Elguero E, Arnathau C, Hidalgo BA, Durand P, Houze S, et al. Human Plasmodium vivax diversity, population structure and evolutionary origin. PLoS Negl Trop Dis. 2020;14:e0008072.

Aregawi M, Cibulskis R, Otten M, Williams R, Dye C. World Malaria Report. World Heal Organization. Geneva: Switzerland; 2008.

Cohen JM, Tatem A, Dlamini S, Novonty JM, Kandula S. Rapid case-based mapping seasonal malaria transmission risk for strategic elimination planning in Swaziland. Malar J. 2013;12:61.

Joao LF, Sergio N, Jorge MM, Marco P. Mapping and modelling malaria risk areas using climate, socio-demographic and clinical variables in Chimoio, Mozambique. Int J Environ Res Public Health. 2018;15:795.

Qayum A, Arya R, Kumar P, Lynn AM. Socio-economic, epidemiological and geographic features based on GIS-integrated mapping to identify malarial hotspots. Malar J. 2015;14:192.

Dwivedi MK, Shyam BS, Shukla R, Sharma NK, Singh PK. GIS Mapping of antimalarial plants based on traditional knowledge in Pushparajgarh Division, District Anuppur, Madhya Pradesh, India. J Herbs Spices Med Plants. 2020;00:1-23.