Spatial-temporal GIS analysis in public health – a case study of polio disease

The purpose of this work was to use spatial-temporal analysis for the prevention and mitigation of disease spread. A prototype application was specifically designed to detect territories with a high incidence of cases and a second was used to validate the results. The first algorithm tried to find clustered cases territories and compare them to the smooth average of the previous two years of data from the same places and their neighbors’. If more cases were detected based on a threshold, then it could be suspected that something unusual was happening. The application would detect such territories and provide alerts to health specialists. The second analysis for validation was using space time cubes method from Arc GIS Pro. It relied on Mann-Kendall and Getis-Ord statistics to detect hot spots territories. The developed analyses have been applied in two cases studies: on the subnational level in Nigeria and in 53 countries belonging to the World Health Organization Regional Office for Europe (WHO Europe). For this reason, the Acute Flaccid Paralysis (AFP) surveillance data collected by the World Health Organization was used corresponding to two indicators: the total number of AFP reported cases and the total numbers of unvaccinated children. The resulting reports have highlighted the underperforming regions in the North-East Nigeria and have spotted two previous outbreaks that occurred in WHO Europe: a large-scale polio outbreak in 2010 started in Tajikistan and a polio outbreak in Israel in 2013. Also, this paper propose a solution on how the developed algorithm could be incorporated into an outbreak prevention system. This would help detecting any future outbreaks.The purpose of this work was to use spatial-temporal analysis for the prevention and mitigation of disease spread. A prototype application was specifically designed to detect territories with a high incidence of cases and a second was used to validate the results. The first algorithm tried to find clustered cases territories and compare them to previous two years of data from the same places and their neighbors’. If more cases were detected based on a threshold, then it could be suspected that something unusual was happening. The application would detect such territories and provide alerts to health specialists. The second analysis for validation was using space time cubes method from Arc GIS Pro software. The developed analyses have been applied in two cases studies: on the subnational level in Nigeria and in 53 countries belonging to the World Health Organization Regional Office for Europe (WHO Europe). For this reason, the Acute Flaccid Paralysis (AFP) surveillance data collected by the World Health Organization was used corresponding to two indicators: the total number of AFP reported cases and the total numbers of unvaccinated children. The resulting reports have highlighted the underperforming regions in the North-East Nigeria and have spotted two previous outbreaks that occurred in WHO Europe: a large-scale polio outbreak in 2010 started in Tajikistan and a polio outbreak in Israel in 2013. Also, this paper propose a solution on how the developed algorithm could be incorporated into an outbreak prevention system. This would help detecting any future outbreaks