International Journal of Environmental Research and Public Health, 2021
The climate is changing, and such changes are projected to cause global increase in the prevalenc... more The climate is changing, and such changes are projected to cause global increase in the prevalence and geographic ranges of infectious diseases such as anthrax. There is limited knowledge in the tropics with regards to expected impacts of climate change on anthrax outbreaks. We determined the future distribution of anthrax in Kenya with representative concentration pathways (RCP) 4.5 and 8.5 for year 2055. Ecological niche modelling (ENM) of boosted regression trees (BRT) was applied in predicting the potential geographic distribution of anthrax for current and future climatic conditions. The models were fitted with presence-only anthrax occurrences (n = 178) from historical archives (2011–2017), sporadic outbreak surveys (2017–2018), and active surveillance (2019–2020). The selected environmental variables in order of importance included rainfall of wettest month, mean precipitation (February, October, December, July), annual temperature range, temperature seasonality, length of lo...
This data record contains of 6 spreadsheets in <b>.csv</b> format, 1 data dictionary ... more This data record contains of 6 spreadsheets in <b>.csv</b> format, 1 data dictionary in <b>.pdf</b> format and 2 questionnaires in <b>.docx </b>format. The data dictionary provides a look-up for the variable names used in the data spreadsheets.These data were produced during a socioeconomic study aiming to measure indicators of poverty, female empowerment and social capital in Kenya The data were gathered from interviews and surveys of 3469 households and 9457 individuals in Gikindu location. Face to face interviews were carried out in February and March, 2018. The data cover aspects such as household characteristics, housing, employment, education, health, agricultural production, food and nutrition, peace and order and individual women characteristics. The six .csv files contain data from three sets of questionnaires: household-level questionnaire, individual woman questionnaire and community-level questionnaire. <b><br></b>The...
Background Anthrax is an important zoonotic disease in Kenya associated with high animal and publ... more Background Anthrax is an important zoonotic disease in Kenya associated with high animal and public health burden and widespread socio-economic impacts. The disease occurs in sporadic outbreaks that involve livestock, wildlife, and humans, but knowledge on factors that affect the geographic distribution of these outbreaks is limited, challenging public health intervention planning. Methods Anthrax surveillance data reported in southern Kenya from 2011 to 2017 were modeled using a boosted regression trees (BRT) framework. An ensemble of 100 BRT experiments was developed using a variable set of 18 environmental covariates and 69 unique anthrax locations. Model performance was evaluated using AUC (area under the curve) ROC (receiver operating characteristics) curves. Results Cattle density, rainfall of wettest month, soil clay content, soil pH, soil organic carbon, length of longest dry season, vegetation index, temperature seasonality, in order, were identified as key variables for pr...
International Journal of Environmental Research and Public Health, 2021
The climate is changing, and such changes are projected to cause global increase in the prevalenc... more The climate is changing, and such changes are projected to cause global increase in the prevalence and geographic ranges of infectious diseases such as anthrax. There is limited knowledge in the tropics with regards to expected impacts of climate change on anthrax outbreaks. We determined the future distribution of anthrax in Kenya with representative concentration pathways (RCP) 4.5 and 8.5 for year 2055. Ecological niche modelling (ENM) of boosted regression trees (BRT) was applied in predicting the potential geographic distribution of anthrax for current and future climatic conditions. The models were fitted with presence-only anthrax occurrences (n = 178) from historical archives (2011–2017), sporadic outbreak surveys (2017–2018), and active surveillance (2019–2020). The selected environmental variables in order of importance included rainfall of wettest month, mean precipitation (February, October, December, July), annual temperature range, temperature seasonality, length of lo...
This data record contains of 6 spreadsheets in <b>.csv</b> format, 1 data dictionary ... more This data record contains of 6 spreadsheets in <b>.csv</b> format, 1 data dictionary in <b>.pdf</b> format and 2 questionnaires in <b>.docx </b>format. The data dictionary provides a look-up for the variable names used in the data spreadsheets.These data were produced during a socioeconomic study aiming to measure indicators of poverty, female empowerment and social capital in Kenya The data were gathered from interviews and surveys of 3469 households and 9457 individuals in Gikindu location. Face to face interviews were carried out in February and March, 2018. The data cover aspects such as household characteristics, housing, employment, education, health, agricultural production, food and nutrition, peace and order and individual women characteristics. The six .csv files contain data from three sets of questionnaires: household-level questionnaire, individual woman questionnaire and community-level questionnaire. <b><br></b>The...
Background Anthrax is an important zoonotic disease in Kenya associated with high animal and publ... more Background Anthrax is an important zoonotic disease in Kenya associated with high animal and public health burden and widespread socio-economic impacts. The disease occurs in sporadic outbreaks that involve livestock, wildlife, and humans, but knowledge on factors that affect the geographic distribution of these outbreaks is limited, challenging public health intervention planning. Methods Anthrax surveillance data reported in southern Kenya from 2011 to 2017 were modeled using a boosted regression trees (BRT) framework. An ensemble of 100 BRT experiments was developed using a variable set of 18 environmental covariates and 69 unique anthrax locations. Model performance was evaluated using AUC (area under the curve) ROC (receiver operating characteristics) curves. Results Cattle density, rainfall of wettest month, soil clay content, soil pH, soil organic carbon, length of longest dry season, vegetation index, temperature seasonality, in order, were identified as key variables for pr...
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