Effects of Socio-Environmental Factors on Malaria Infection in Pakistan: A Bayesian Spatial Analysis

Muhammad Farooq Umer, Shumaila Zofeen, Abdul Majeed, Wenbiao Hu, Xin Qi and Guihua Zhuang
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Muhammad Farooq Umer: School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
Shumaila Zofeen: School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
Abdul Majeed: Directorate of Malaria Control Program, Islamabad 44000, Pakistan
Wenbiao Hu: School of Public Health and Social Work, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia
Xin Qi: School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
Guihua Zhuang: School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China

IJERPH, 2019, vol. 16, issue 8, 1-12

Abstract: The role of socio-environmental factors in shaping malaria dynamics is complex and inconsistent. Effects of socio-environmental factors on malaria in Pakistan at district level were examined. Annual malaria cases data were obtained from Directorate of Malaria Control Program, Pakistan. Meteorological data were supplied by Pakistan Meteorological Department. A major limitation was the use of yearly, rather than monthly/weekly malaria data in this study. Population data, socio-economic data and education score data were downloaded from internet. Bayesian conditional autoregressive model was used to find the statistical association of socio-environmental factors with malaria in Pakistan. From 136/146 districts in Pakistan, >750,000 confirmed malaria cases were included, over a three years’ period (2013–2015). Socioeconomic status ((posterior mean value −3.965, (2.5% quintile, −6.297%), (97.5% quintile, −1.754%)) and human population density (−7.41 × 10 −4 , −0.001406%, −1.05 × 10 −4 %) were inversely related, while minimum temperature (0.1398, 0.05275%, 0.2145%) was directly proportional to malaria in Pakistan during the study period. Spatial random effect maps presented that moderate relative risk (RR, 0.75 to 1.24) and high RR (1.25 to 1.99) clusters were scattered throughout the country, outnumbering the ones’ with low RR (0.23 to 0.74). Socio-environmental variables influence annual malaria incidence in Pakistan and needs further evaluation.

Keywords: Socio-climate variables; malaria; Pakistan; Bayesian CAR model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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