Projecting Malaria Incidence Based on Climate Change Modeling Approach: A Systematic Review

Mazni Baharom; Sharifah Saffinas Syed Soffian; Chua Su Peng; Mohd Hafiz Baharudin; Ummi Mirza; Mohd Faizal Madrim; Mohammad Saffree Jeffree; Syed Sharizman Syed Abdul Rahim; Mohd Rohaizat Hassan

doi:10.3889/oamjms.2022.10141

Authors

Mazni Baharom Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia
Sharifah Saffinas Syed Soffian Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia https://orcid.org/0000-0003-2721-3084
Chua Su Peng Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia https://orcid.org/0000-0002-9460-5929
Mohd Hafiz Baharudin Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia
Ummi Mirza Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia https://orcid.org/0000-0001-9170-3155
Mohd Faizal Madrim Department of Public Health Medicine, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
Mohammad Saffree Jeffree Department of Public Health Medicine, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
Syed Sharizman Syed Abdul Rahim Department of Public Health Medicine, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia https://orcid.org/0000-0002-9090-2563
Mohd Rohaizat Hassan Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.3889/oamjms.2022.10141

Keywords:

Projection, Malaria incidence, Climate change, Modelling, Public health

Abstract

BACKGROUND: Climate change will affect the transmission of malaria by shifting the geographical space of the vector.

AIM: The review aims to examine the climate change modeling approach and climatic variables used for malaria projection.

METHODS: Articles were systematically searched from four databases, Scopus, Web of Science, PubMed, and SAGE. The PICO concept was used for formulation search and PRISMA approach to identify the final articles.

RESULTS: A total of 27 articles were retrieved and reviewed. There were six climate factors identified in this review: Temperature, rainfall/precipitation, humidity, wind, solar radiation, and climate change scenarios. Modeling approaches used to project future malarial trend includes mathematical and computational approach.

CONCLUSION: This review provides robust evidence of an association between the impact of climate change and malaria incidence. Prediction on seasonal patterns would be useful for malaria surveillance in public health prevention and mitigation strategies.

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References

World Health Organization. Malaria. Geneva: World Health Organization; 2021.

Rejeki DS, Wijayanti SP, Octaviana D, Suratman S. The effect of climate and intervention methods on malaria incidence: A time series analysis. Ann Trop Med Public Health. 2019;22(11):123-9. https://doi.org/10.36295/ASRO.2019.221117 DOI: https://doi.org/10.36295/ASRO.2019.221117

Bouma MJ, Poveda G, Rojas W, Chavasse D, Quiñones M, Cox J, et al. Predicting high-risk years for malaria in Colombia using parameters of El Nino Southern Oscillation. Trop Med Int Health. 1997;2(12):1122-7. https://doi.org/10.1046/j.1365-3156.1997.d01-210.x PMid:9438466 DOI: https://doi.org/10.1046/j.1365-3156.1997.d01-210.x

Huang F, Zhou S, Zhang S, Wang H, Tang L. Temporal correlation analysis between malaria and meteorological factors in Motuo County, Tibet. Malar J. 2011;10:54. https://doi.org/10.1186/1475-2875-10-54 PMid:21375751 DOI: https://doi.org/10.1186/1475-2875-10-54

Paaijmans KP, Read AF, Thomas MB. Understanding the link between malaria risk and climate. Proc Natl Acad Sci USA. 2009;106(33):13844-9. https://doi.org/10.1073/pnas.0903423106 PMid:19666598 DOI: https://doi.org/10.1073/pnas.0903423106

Patz JA, Olson SH. Malaria risk and temperature: Influences from global climate change and local land use practices. Proc Natl Acad Sci U S A. 2006;103(15):5635-6. https://doi.org/10.1073/pnas.0601493103 PMid:16595623 DOI: https://doi.org/10.1073/pnas.0601493103

Alemu A, Abebe G, Tsegaye W, Golassa L. Climatic variables and malaria transmission dynamics in Jimma town, South West Ethiopia. Parasit Vectors. 2011;4(1):30. https://doi.org/10.1186/1756-3305-4-30 PMid:21366906 DOI: https://doi.org/10.1186/1756-3305-4-30

Rabinovich RN, Drakeley C, Djimde AA, Hall BF, Hay SI, Hemingway J, et al. The malERA Consultative Group on Vaccines. A research agenda for malaria eradication: Vaccines. PLoS Med. 2011;8:e1000398. DOI: https://doi.org/10.1371/journal.pmed.1000398

Hay SI, Cox J, Rogers DJ, Randolph SE, Stern DI, Shanks GD, et al. Climate change and the resurgence of malaria in the East African highlands. Nature. 2002;415(6874):905-9. https://doi.org/10.1038/415905a PMid:11859368 DOI: https://doi.org/10.1038/415905a

Ssempiira J, Kissa J, Nambuusi B, Mukooyo E, Opigo J, Makumbi F, et al. Interactions between climatic changes and intervention effects on malaria spatio-temporal dynamics in Uganda. Parasite Epidemiol Control. 2018;3(3):e00070. https://doi.org/10.1016/j.parepi.2018.e00070 PMid:29988311 DOI: https://doi.org/10.1016/j.parepi.2018.e00070

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71 DOI: https://doi.org/10.1136/bmj.n71

Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The mixed methods appraisal tool (MMAT) version 2018 for information professionals and researchers. Educ Inform. 2018;34(4):285-91. DOI: https://doi.org/10.3233/EFI-180221

Lockwood C, Munn Z, Porritt K. Qualitative research synthesis: Methodological guidance for systematic reviewers utilizing metaaggregation. Int J Evid Based Healthc. 2015;13(3):179-87. https://doi.org/10.1097/XEB.0000000000000062 PMid:26262565 DOI: https://doi.org/10.1097/XEB.0000000000000062

Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane handbook for systematic reviews of interventions. In: Cochrane Handbook for Systematic Reviews of Interventions.Hoboken: A John Wiley and Sons; 2019. DOI: https://doi.org/10.1002/9781119536604

Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77-101. DOI: https://doi.org/10.1191/1478088706qp063oa

Flemming K, Booth A, Garside R, Tunçalp Ö, Noyes J. Qualitative evidence synthesis for complex interventions and guideline development: Clarification of the purpose, designs and relevant methods. BMJ Glob Health. 2019;4(Suppl 1):e000882. https://doi.org/10.1136/bmjgh-2018-000882 PMid:30775015 DOI: https://doi.org/10.1136/bmjgh-2018-000882

Vaismoradi M, Turunen H, Bondas T. Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nurs Health Sci. 2013;15(3):398-405. https://doi.org/10.1111/nhs.12048 PMid:23480423 DOI: https://doi.org/10.1111/nhs.12048

Messina JP, Brady OJ, Pigott DM, Golding N, Kraemer MU, Scott TW, et al. The many projected futures of dengue. Nat Rev Microbiol. 2015;13(4):230-9. https://doi.org/10.1038/nrmicro3430 PMid:25730702 DOI: https://doi.org/10.1038/nrmicro3430

Ermert V, Fink AH, Morse AP, Paeth H. The impact of regional climate change on malaria risk due to greenhouse forcing and land-use changes in tropical Africa. Environ Health Perspect. 2012;120(1):77-84. https://doi.org/10.1289/ehp.1103681 PMid:21900078 DOI: https://doi.org/10.1289/ehp.1103681

Karuri SW, Snow RW. Forecasting paediatric malaria admissions on the Kenya Coast using rainfall. Glob Health Action. 2016;9(1):29876. https://doi.org/10.3402/gha.v9.29876 PMid:26842613 DOI: https://doi.org/10.3402/gha.v9.29876

Le PV, Kumar P, Ruiz MO, Mbogo C, Muturi EJ. Predicting the direct and indirect impacts of climate change on malaria in coastal Kenya. PLoS One. 2019;14(2):e0211258. https://doi.org/10.1371/journal.pone.0211258 PMid:30726279 DOI: https://doi.org/10.1371/journal.pone.0211258

Gao HW, Wang LP, Liang S, Liu YX, Tong SL, Wang JJ, et al. Change in rainfall drives malaria re-emergence in Anhui province, China. PLoS One. 2012;7(8):e43686. https://doi.org/10.1371/journal.pone.0043686 PMid:22928015 DOI: https://doi.org/10.1371/journal.pone.0043686

Yamana TK, Eltahir EA. Projected impacts of climate change on environmental suitability for malaria transmission in West Africa. Environ Health Perspect. 2013;121(10):1179-86. https://doi.org/10.1289/ehp.1206174 PMid:24043443 DOI: https://doi.org/10.1289/ehp.1206174

Bouma MJ, Siraj AS, Rodo X, Pascual M. El Niño-based malaria epidemic warning for Oromia, Ethiopia, from August 2016 to July 2017. Trop Med Int Health. 2016;21(11):1481-8. https://doi.org/10.1111/tmi.12776 PMid:27580403 DOI: https://doi.org/10.1111/tmi.12776

Moss R, Babiker M, Brinkman S, Calvo E, Carter T, Edmonds J, et al. Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts and Response Strategies. London: IPCC Expert Meeting Report; 2008.

Ferrão JL, Mendes JM, Painho M. Modelling the influence of climate on malaria occurrence in Chimoio Municipality, Mozambique. Parasit Vectors. 2017;10(1):260. https://doi.org/10.1186/s13071-017-2205-6 DOI: https://doi.org/10.1186/s13071-017-2205-6

Mopuri R, Kakarla SG, Mutheneni SR, Kadiri MR, Kumaraswamy S. Climate based malaria forecasting system for Andhra Pradesh, India. J Parasit Dis. 2020;44(3):497-510. https://doi.org/10.1007/s12639-020-01216-6 PMid:32801501 DOI: https://doi.org/10.1007/s12639-020-01216-6

Siraj AS, Santos-Vega M, Bouma MJ, Yadeta D, Ruiz Carrascal D, Pascual M. Altitudinal changes in malaria incidence in highlands of Ethiopia and Colombia. Science. 2014;343(6175):1154-8. https://doi.org/10.1126/science.1244325 PMid:24604201 DOI: https://doi.org/10.1126/science.1244325

Pachauri RK, Gomez-Echeverri L, Riahi K. Synthesis report: Summary for policy makers. In: Climate Change 2014: Mitigation of Climate Change. IPCC Working Group III Contribution to AR5. Telangana: University Press; 2014.

Kwak J, Noh H, Kim S, Singh VP, Hong SJ, Kim D, et al. Future climate data from RCP 4.5 and occurrence of malaria in Korea. Int J Environ Res Public Health. 2014;11(10):10587-605. https://doi.org/10.3390/ijerph111010587 PMid:25321875 DOI: https://doi.org/10.3390/ijerph111010587

Leedale J, Tompkins AM, Caminade C, Jones AE, Nikulin G, Morse AP. Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty. Geospat Health. 2016;11(Suppl 1):393. https://doi.org/10.4081/gh.2016.393 PMid:27063736 DOI: https://doi.org/10.4081/gh.2016.393

Alimi TO, Fuller DO, Qualls WA, Herrera SV, Arevalo-Herrera M, Quinones ML, et al. Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population. Parasit Vectors. 2015;8(1):431. https://doi.org/10.1186/s13071-015-1033-9 PMid:26289677 DOI: https://doi.org/10.1186/s13071-015-1033-9

Anwar MY, Lewnard JA, Parikh S, Pitzer VE. Time series analysis of malaria in Afghanistan: Using ARIMA models to predict future trends in incidence. Malar J. 2016;15(1):556. https://doi.org/10.1186/s12936-016-1602-1 DOI: https://doi.org/10.1186/s12936-016-1602-1

Boateng RA, Tastan Bishop Ö, Musyoka TM. Characterisation of plasmodial transketolases and identification of potential inhibitors: An in silico study. Malar J. 2020;19(1):442. https://doi.org/10.1186/s12936-020-03512-1 PMid:33256744 DOI: https://doi.org/10.1186/s12936-020-03512-1

Kim Y, Ratnam JV, Doi T, Morioka Y, Behera S, Tsuzuki A, et al. Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model. Sci Rep. 2019;9(1):17882. https://doi.org/10.1038/s41598-019-53838-3 PMid:31784563 DOI: https://doi.org/10.1038/s41598-019-53838-3

Palaniyandi M. The role of remote sensing and GIS for spatial prediction of vector-borne diseases transmission: A systematic review. J Vector Borne Dis. 2012;49(4):197-204. PMid:23428518

Diouf I, Rodriguez-Fonseca B, Deme A, Caminade C, Morse AP, Cisse M, et al. Comparison of malaria simulations driven by meteorological observations and reanalysis products in Senegal. Int J Environ Res Public Health. 2017;14(10):1119. https://doi.org/10.3390/ijerph14101119 PMid:28946705 DOI: https://doi.org/10.3390/ijerph14101119

Carvalho BM, Rangel EF, Vale MM. Evaluation of the impacts of climate change on disease vectors through ecological niche modelling. Bull Entomol Res. 2017;107(4):419-30. https://doi.org/10.1017/S0007485316001097 PMid:27974065 DOI: https://doi.org/10.1017/S0007485316001097

Dabaro D, Birhanu Z, Negash A, Hawaria D, Yewhalaw D. Effects of rainfall, temperature and topography on malaria incidence in elimination targeted district of Ethiopia. Malar J. 2021;20(1):104. https://doi.org/10.1186/s12936-021-03641-1 PMid:33608004 DOI: https://doi.org/10.1186/s12936-021-03641-1

Ostovar A, Haghdoost AA, Rahimiforoushani A, Raeisi A, Majdzadeh R. Time series analysis of meteorological factors influencing Malaria in south eastern Iran. J Arthropod Borne Dis. 2016;10(2):222-36. PMid:27308280

Ateba FF, Febrero-Bande M, Sagara I, Sogoba N, Touré M, Sanogo D, et al. Predicting malaria transmission dynamics in dangassa, mali: A novel approach using functional generalized additive models. Int J Environ Res Public Health. 2020;17(17):6339. https://doi.org/10.3390/ijerph17176339 PMid:32878174 DOI: https://doi.org/10.3390/ijerph17176339

Darkoh EL, Larbi JA, Lawer EA. A weather-based prediction model of Malaria prevalence in Amenfi West district, Ghana. Malar Res Treat. 2017;2017:7820454. https://doi.org/10.1155/2017/7820454 PMid:28255497 DOI: https://doi.org/10.1155/2017/7820454

Das S, Saha TR, Poddar S, Das S. Malaria in India: A predictive study. Malays J Med Health Sci. 2020;16(Suppl 10):25-29.

Xu Z, Bambrick H, Frentiu FD, Devine G, Yakob L, Williams G, et al. Projecting the future of dengue under climate change scenarios: Progress, uncertainties and research needs. PLoS Negl Trop Dis. 2020;14(3):e0008118. https://doi.org/10.1371/journal.pntd.0008118 PMid:32119666 DOI: https://doi.org/10.1371/journal.pntd.0008118