Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria
<i>Background</i>: despite the increase in malaria control and elimination efforts, weather patterns and ecological factors continue to serve as important drivers of malaria transmission dynamics. This study examined the statistical relationship between weather variables and malaria inci...
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doaj-27e0fefe9c05415bb44711a666ee81112020-11-25T03:27:08ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012020-05-01173474347410.3390/ijerph17103474Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, NigeriaOguntade Emmanuel Segun0Shamarina Shohaimi1Meenakshii Nallapan2Alaba Ajibola Lamidi-Sarumoh3Nader Salari4Institute for Mathematical Research, Universiti Putra Malaysia, Serdang 43400, Selangor, MalaysiaInstitute for Mathematical Research, Universiti Putra Malaysia, Serdang 43400, Selangor, MalaysiaDepartment of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Selangor, MalaysiaDepartment of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Selangor, MalaysiaDepartment of Biostatistics, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah 6715847141, Iran<i>Background</i>: despite the increase in malaria control and elimination efforts, weather patterns and ecological factors continue to serve as important drivers of malaria transmission dynamics. This study examined the statistical relationship between weather variables and malaria incidence in Abuja, Nigeria. <i>Methodology/Principal Findings</i>: monthly data on malaria incidence and weather variables were collected in Abuja from the year 2000 to 2013. The analysis of count outcomes was based on generalized linear models, while Pearson correlation analysis was undertaken at the bivariate level. The results showed more malaria incidence in the months with the highest rainfall recorded (June–August). Based on the negative binomial model, every unit increase in humidity corresponds to about 1.010 (95% confidence interval (CI), 1.005–1.015) times increase in malaria cases while the odds of having malaria decreases by 5.8% for every extra unit increase in temperature: 0.942 (95% CI, 0.928–0.956). At lag 1 month, there was a significant positive effect of rainfall on malaria incidence while at lag 4, temperature and humidity had significant influences. <i>Conclusions:</i> malaria remains a widespread infectious disease among the local subjects in the study area. Relative humidity was identified as one of the factors that influence a malaria epidemic at lag 0 while the biggest significant influence of temperature was observed at lag 4. Therefore, emphasis should be given to vector control activities and to create public health awareness on the proper usage of intervention measures such as indoor residual sprays to reduce the epidemic especially during peak periods with suitable weather conditions.https://www.mdpi.com/1660-4601/17/10/3474negative binomial modelsweather variablesmalariaNigeria |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Oguntade Emmanuel Segun Shamarina Shohaimi Meenakshii Nallapan Alaba Ajibola Lamidi-Sarumoh Nader Salari |
spellingShingle |
Oguntade Emmanuel Segun Shamarina Shohaimi Meenakshii Nallapan Alaba Ajibola Lamidi-Sarumoh Nader Salari Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria International Journal of Environmental Research and Public Health negative binomial models weather variables malaria Nigeria |
author_facet |
Oguntade Emmanuel Segun Shamarina Shohaimi Meenakshii Nallapan Alaba Ajibola Lamidi-Sarumoh Nader Salari |
author_sort |
Oguntade Emmanuel Segun |
title |
Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria |
title_short |
Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria |
title_full |
Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria |
title_fullStr |
Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria |
title_full_unstemmed |
Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria |
title_sort |
statistical modelling of the effects of weather factors on malaria occurrence in abuja, nigeria |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1661-7827 1660-4601 |
publishDate |
2020-05-01 |
description |
<i>Background</i>: despite the increase in malaria control and elimination efforts, weather patterns and ecological factors continue to serve as important drivers of malaria transmission dynamics. This study examined the statistical relationship between weather variables and malaria incidence in Abuja, Nigeria. <i>Methodology/Principal Findings</i>: monthly data on malaria incidence and weather variables were collected in Abuja from the year 2000 to 2013. The analysis of count outcomes was based on generalized linear models, while Pearson correlation analysis was undertaken at the bivariate level. The results showed more malaria incidence in the months with the highest rainfall recorded (June–August). Based on the negative binomial model, every unit increase in humidity corresponds to about 1.010 (95% confidence interval (CI), 1.005–1.015) times increase in malaria cases while the odds of having malaria decreases by 5.8% for every extra unit increase in temperature: 0.942 (95% CI, 0.928–0.956). At lag 1 month, there was a significant positive effect of rainfall on malaria incidence while at lag 4, temperature and humidity had significant influences. <i>Conclusions:</i> malaria remains a widespread infectious disease among the local subjects in the study area. Relative humidity was identified as one of the factors that influence a malaria epidemic at lag 0 while the biggest significant influence of temperature was observed at lag 4. Therefore, emphasis should be given to vector control activities and to create public health awareness on the proper usage of intervention measures such as indoor residual sprays to reduce the epidemic especially during peak periods with suitable weather conditions. |
topic |
negative binomial models weather variables malaria Nigeria |
url |
https://www.mdpi.com/1660-4601/17/10/3474 |
work_keys_str_mv |
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1724589266505302016 |