TY - JOUR
T1 - Effects of Socio-Environmental Factors on Malaria Infection in Pakistan
T2 - A Bayesian Spatial Analysis
AU - Umer, Muhammad Farooq
AU - Zofeen, Shumaila
AU - Majeed, Abdul
AU - Hu, Wenbiao
AU - Qi, Xin
AU - Zhuang, Guihua
N1 - Publisher Copyright:
© 2019 by the authors.
PY - 2019/4/2
Y1 - 2019/4/2
N2 - 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 x 10-4, -0.001406%, -1.05 x 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.
AB - 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 x 10-4, -0.001406%, -1.05 x 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.
KW - Bayesian CAR model
KW - Malaria
KW - Pakistan
KW - Socio-climate variables
UR - https://www.scopus.com/pages/publications/85065088095
U2 - 10.3390/ijerph16081365
DO - 10.3390/ijerph16081365
M3 - 文章
C2 - 30995744
AN - SCOPUS:85065088095
SN - 1661-7827
VL - 16
JO - International Journal of Environmental Research and Public Health
JF - International Journal of Environmental Research and Public Health
IS - 8
M1 - 1365
ER -