Spatiotemporal clustering of cutaneous leishmaniasis in Fars province,Iran

Objective: To assess the spatiotemporal trait of cutaneous leishmaniasis(CL) in Fars province, Iran.Methods: Spatiotemporal cluster analysis was conducted retrospectively to find spatiotemporal clusters of CL cases. Time-series data were recorded from 29 201 cases in Fars province, Iran from 2010 to 2015, which were used to verify if the cases were distributed randomly over time and place. Then, subgroup analysis was applied to find significant sub-clusters within large clusters. Spatiotemporal permutation scans statistics in addition to subgroup analysis were implemented using Sa TScan software.Results: This study resulted in statistically significant spatiotemporal clusters of CL(P < 0.05). The most likely cluster contained 350 cases from 1 July 2010 to 30 November2010. Besides, 5 secondary clusters were detected in different periods of time. Finally,statistically significant sub-clusters were found within the three large clusters(P < 0.05).Conclusions: Transmission of CL followed spatiotemporal pattern in Fars province,Iran. This can have an important effect on future studies on prediction and prevention of CL.

High-risk spatiotemporal patterns of cutaneous leishmaniasis:a nationwide study in Iran from 2011 to 2020

Background Cutaneous leishmaniasis(CL)is a wide-reaching infection of major public health concern.Iran is one of the six most endemic countries in the world.This study aims to provide a spatiotemporal visualization of CL cases in Iran at the county level from 2011 to 2020,detecting high-risk zones,while also noting the movement of high-risk clusters.Methods On the basis of clinical observations and parasitological tests,data of 154,378 diagnosed patients were obtained from the Iran Ministry of Health and Medical Education.Utilizing spatial scan statistics,we investigated the disease’s purely temporal,purely spatial,spatial variation in temporal trends and spatiotemporal patterns.At P=0.05 level,the null hypothesis was rejected in every instance.Results In general,the number of new CL cases decreased over the course of the 9-year research period.From 2011 to 2020,a regular seasonal pattern,with peaks in the fall and troughs in the spring,was found.The period of September–February of 2014–2015 was found to hold the highest risk in terms of CL incidence rate in the whole country[relative risk(RR)=2.24,P<0.001)].In terms of location,six signifcant high-risk CL clusters covering 40.6%of the total area of the country were observed,with the RR ranging from 1.87 to 9.69.In addition,spatial variation in the temporal trend analysis found 11 clusters as potential high-risk areas that highlighted certain regions with an increasing tendency.Finally,fve space-time clusters were found.The geographical displacement and spread of the disease followed a moving pattern over the 9-year study period afecting many regions of the country.Conclusions Our study has revealed signifcant regional,temporal,and spatiotemporal patterns of CL distribution in Iran.Over the years,there have been multiple shifts in spatiotemporal clusters,encompassing many diferent parts of the country from 2011 to 2020.The results reveal the formation of clusters across counties that cover certain parts of provinces,indicating the importance of conducting spatiotemporal analyses at the county level for studies that encompass entire countries.Such analyses,at a fner geographical scale,such as county level,might provide more precise results than analyses at the scale of the province.

Spatial and temporal distribution of American cutaneous leishmaniasis in Acre state,Brazil

Background:Acre has reported the highest incidence of American cutaneous leishmaniasis(ACL)in Brazil in recent years.The present study seeks to identify high and low risk agglomerations of ACL in space and space-time during the period from 2007 to 2013 in Acre,and also to characterize the occurrence of the disease in time and according to sociodemographic variables.Methods:This is an ecological study,the study population of which consisted of autochthonous ACL cases notified in the municipalities of Acre by an epidemiological surveillance system.Scan statistics of SaTScan^(TM)software were used to identify spatial and space-time clusters.In addition,the cases were characterized by sex,age,home situation(in a rural or urban area),and temporal tendency.Results:Acre reported an incidence rate of 12.4 cases per 10000 inhabitant-years in the study period,with the rates varied greatly(standard deviation of 21.8)among their 22 municipalities.One agglomeration of high risk and three of low risk were detected in space and space-time.Four of the five micro-regions of Acre presented a stationary temporal tendency.The profile of transmission varied according to the micro-region.Generally speaking,the disease occurred more often among young people,those of male gender,and those living in rural areas.Conclusions:Acre has stood out within the Brazilian national context due to its high rates of ACL incidence in the central region of the Acre Valley.The high rates in the micro-region of Brasileia are related to the disease’s intra/peridomiciliary occurrence,and it would seem that the municipality of Sena Madureira is approaching a transmission pattern similar to that of Brasileia.In other micro-regions,the profile of the disease’s transmission is mainly related to the forest/sylvatic cycle of ACL.

Spatio-temporal clustering analysis of COVID-19 cases in Johor

At the end of the year 2019,a virus named SARS-CoV-2 induced the coronavirus disease,which is very contagious and quickly spread around the world.This new infectious disease is called COVID-19.Numerous areas,such as the economy,social services,education,and healthcare system,have suffered grave consequences from the invasion of this deadly virus.Thus,a thorough understanding of the spread of COVID-19 is required in order to deal with this outbreak before it becomes an infectious disaster.In this research,the daily reported COVID-19 cases in 92 sub-districts in Johor state,Malaysia,as well as the population size associated to each sub-district,are used to study the propagation of COVID-19 disease across space and time in Johor.The time frame of this research is about 190 days,which started from August 5,2021,until February 10,2022.The clustering technique known as spatio-temporal clustering,which considers the spatio-temporal metric was adapted to determine the hot-spot areas of the COVID-19 disease in Johor at the sub-district level.The results indicated that COVID-19 disease does spike in the dynamic populated sub-districts such as the state's economic centre(Bandar Johor Bahru),and during the festive season.These findings empirically prove that the transmission rate of COVID-19 is directly proportional to human mobility and the presence of holidays.On the other hand,the result of this study will help the authority in charge in stopping and preventing COVID-19 from spreading and become worsen at the national level.