SaTScan Software Research Articles

Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA.

Incidence of Legionnaires’ disease is increasing, particularly in the Mid-Atlantic states in the United States; since 2015, New Jersey has documented ≈250–350 legionellosis cases per year. We used SaTScan software to develop a semiautomated surveillance tool for prospectively detecting legionellosis clusters in New Jersey. We varied temporal window size and baseline period to evaluate optimal parameter selections. The surveillance system detected 3 community clusters of Legionnaires’ disease that were subsequently investigated. Other, smaller clusters were detected, but standard epidemiologic data did not identify common sources or new cases. The semiautomated processing is straightforward and replicable in other jurisdictions, likely by persons with even basic programming skills.

Spatial distribution and determinant factors of intimate partner violence among reproductive age group women in Ethiopia: Using generalized structural equation modeling.

IntroductionIntimate Partner Violence (IPV) is the most serious and pervasive yet under-recognized human rights violation in the world, particularly in Ethiopia. Hence, the objective of this study was to find the spatial distribution of IPV and its determinant factors in Ethiopia.MethodsSecondary data analysis was conducted among 2,687 reproductive age group women (15–49 years). The distribution of IPV across the country was observed by ArcGIS software. In SaTScan software, the Bernoulli model was fitted by Kulldorff methods to identify the purely spatial clusters of IPV. Besides, Generalized Structural Equation Model (GSEM) was used to determine factors associated with each domain of IPV (physical, emotional & sexual violence).ResultThe spatial distribution of IPV was found to be clustered in Ethiopia with Global Moran’s I 0.09 (p < 0.001), and the highest IPV cluster was observed in Oromia (p < 0.001), Somali (p < 0.001) and SNNP (p<0.001) regions. Watching television and not having attitudes toward wife beating were negatively associated with physical violence. Being rich and nonsmoker were inversely associated with emotional violence. The odds of experiencing sexual violence were high among pregnant women and wives of uneducated husbands/partners. In addition, women’s decision-making autonomy and husband/partner drinking alcohol have positive and negative associations with all domains of IPV respectively.ConclusionThere was a significant clustering of IPV in Ethiopia and the highest IPV cluster was observed in Oromia, Somali and SNNP regions. Being rich, watching television, not having attitudes toward wife beating, women’s decision-making autonomy, and husband’s/partner’s high education and non-alcohol drinker status were negatively associated with IPV. The likelihood of experiencing IPV was also high among smokers and pregnant women. Thus, we recommend that improving the economic status of the household through social protection and empowerment of women in decision-making autonomy by education and employment and increasing community awareness about the consequences of IPV with particular emphasis on Oromia, Somali and SNNP regions is essential.

Spatial Cluster Analysis of Stomach Neoplasms in the Center of Iran Based on a Population-Based Study, 2009-2014: Application of the Poisson-Based Probability Model.

Background:A better understanding of the spatial pattern of stomach cancer can be helpful in the implementation of preventive strategies. This study is one of the first studies to establish a study unit based on the smallest possible size for cluster analysis. This study includes a novel evaluation of spatial differences in different geographical areas of Arak. The present study seeks to discover the spatial clusters of stomach cancer from 2009 to 2014 in Arak.Methods:All of the addresses of the stomach cancer cases were geocoded. After that, the number of stomach cancer cases in each census block was calculated to be entered in the SaTScan software. A discrete Poisson-based probability model was used to analyze this cluster.Results:In Arak, there are 5502 census blocks with a population of about 526,182. The number of identified and registered stomach cancer cases with an acceptable residence address was 392. Totally, 11 stomach cancer clusters were established in the area of Arak, from these; two clusters were detected statistically significant. Relative risks of the first and second clusters were 1.75 (P = 0.01) and 17.60 (P = 0.04) and those are located within the radius of 1.73 and 0.085 km, respectively.Conclusions:Our results have confirmed that two areas are at a higher risk than others. However, based on the results of this study, community-based interventions in certain geographical areas can be designed to reduce and control the incidence of stomach cancer.

Spatial and Space-time Clustering of Diarrhoeal Cases among Under-Five Children in Karkala, Karnataka: A Geospatial Analysis

Introduction: Globally, India tops by contributing the maximum number of diarrhoeal fatality. Forecasting the path and spread of diarrhoeal disease is critical due to its multifactorial cause, which needs robust spatial analysis and experiential investigations of communicable disease. Aim: To investigate purely spatial, purely temporal, and spacetime clusters of diarrhoea among under-five children using a Geographic Information System (GIS) in Karkala taluk of the Udupi district of Karnataka, India. Materials and Methods: A retrospective longitudinal study was conducted involving all the primary health centres of Karkala taluk by the investigators, from the Department of Public Health, K S Hegde Medical Academy, Nitte (DU), Mangalore, Karnataka, India. The data on diarrhoea among under-five children was collected for three years, i.e., from 1st April 2015 to 31st March 2018, at the Udupi district health office. A total of 49 village data were obtained, and 3894 under-five childhood diarrhoea were reported during the study period. The annual incidence of childhood diarrhoea at the taluk level was calculated using excel. The spatial, temporal and space-time diarrhoeal clusters were identified using Kulldorff SaTScan software. Geographic Information System, QGIS 3.20.2 software was used to plot the maps. Results: The analysis of the spatial cluster using SaTScan software for three years in the study area identified eight highrisk areas (p-value&lt;0.0001), covering 17 villages. The most likely spatiotemporal cluster region was located at the northern Karkala, and the most-at-risk period was 1st April 2016 to 30th September 2017 {Log Likelihood Ratio (LLR) =114.67 and p-value &lt;0.00001}. The analysis of purely temporal cluster showed that one most likely cluster happened in all villages (LLR= 73.89, p-value &lt;0.001) from 1st April 2017 to 3rd March 2018. Conclusion: The diarrhoea among under-five children at Karkala taluk was not randomly distributed over space and time.

INCIDENCE AND LETHALITY OF COVID-19 CLUSTERS IN BRAZIL VIA CIRCULAR SCAN METHOD

The COVID-19 pandemic has spread rapidly around the world in a frightening way. In Brazil, the third country with the highest number of infected and deaths from the disease, it is important for government health authorities to identify the federation units that stand out in cases and deaths from this disease to target resources. The circular scan statistic proposed by Martin Kulldorff allows to identify with some statistical significance the units of the federation that stand out in relation to the number of cases and deaths of COVID-19 in Brazil. Such units of federation are known as clusters. Once these clusters were identified, we used the coefficients of incidence and lethality to better describe the behavior of these clusters during three phases of the pandemic: the initial phase, the peak phase, and also the stability and fall phase. We observed changes in the location of the clusters identified in these three phases and used the R software and also the SaTScan software to obtain the maps and results, which were consistent with what was reported by the Brazilian media.

Socio-Epidemiological Features and Spatial Distribution of Malaria in an Area under Mining Activity in the Brazilian Amazon Region.

Malaria is an acute febrile infectious disease that represents an important public health problem in the Brazilian amazon region. The present study described the socio-epidemiological and spatial characteristics of malaria in a population from the Tapajós mining areas, Pará, Brazilian Amazon. A cross-sectional study, including individuals from Itaituba city, an area under mining activity influence, was conducted. The geographic coordinates were obtained in the field using the Global Positioning System (GPS) Garmin 78csx; for spatial analysis, we used the Kernel Density Estimator with the application of scanning statistics with the SaTScan software. Of the 908 individuals, 311 were positive for malaria. Most of the malaria cases were associated with male individuals, gold miners and with a monthly income of 4-6 salaries. Binary logistic regression analysis demonstrated that gold miners were nearly five times more likely to acquire malaria. In addition, a context of risk for sexually transmitted infections, substance abuse and poor support conditions was observed, worsening the healthcare scenario in this endemic area for malaria. The spatial distribution of malaria cases is irregular in the municipality with hotspot areas located in the Amana Flona that coincide with areas of illegal mining and high human mobility. Finally, the presented socio-epidemiological and spatial distribution data may aid in the development of more effective control measures for malaria in the area.

Spatial analysis studies of endemic diseases for health surveillance: Application of scan statistics for surveillance of tuberculosis among residents of a metropolitan municipality aged 60 years and above

Abstract Health surveillance aims to monitor adverse health events, and to set disease prevention and control goals, especially for communicable diseases, such as tuberculosis (TB). Older people have a higher risk of TB, due to their specific characteristics, whichpredispose them to infectious disease. Thus, the objective of this study was to demonstrate the importance of scan statistics for detecting spatiotemporal clusters of TB. We conducted a quantitative is an ecological, descriptive study, with a quantitative approach, using the spatial analysis techniques, specifically scan statistics. The study was conducted in the municipality of Belém, Pará, in Brazil using data on 1,134 new cases of TB diagnosed in individuals aged ≥60 years from 2011 to 2015.The data were analyzed using SaTScan software. The analysis of the spatiotemporal dynamics of TB in the municipality showed thatthe high-risk areas includedthe most densely populated neighborhoods, highlighting the priority of theseareas for disease control measures. Spatial analysis can be used to guide more effective interventions according to the characteristics of the location and the local population.

1472Spatial clusters and affecting factors on Alzheimer's disease death in South Korea

Abstract Background The prevalence of dementia is increasing worldwide; and dementia deaths are also increasing. In South Korea, deaths from Alzheimer's disease (AD) ranked 9th in the 2018 cause of death statistics, and the ranking has risen. Methods We collected 2009 to 2018 AD deaths and related data from Statistics Korea and Community Health Survey. SaTScan software was used for detecting and evaluating the clusters with high risk in AD deaths, and R version 4.0.3 was used for mapping and analysis of affecting factors. Results A total of 39,412 people died from AD during 10 years in Korea, 7.7 per 100,000 inhabitants. While 98.7% of deaths were above-65 age, the proportion of under 65 was also rising. The global Moran index of 10 years’ AD deaths was 0.2 (P &amp;lt; 0.01), and the clusters were detected primarily in southern rural region. According to the spatial regression analysis, AD deaths in 2018 were increased in area with lower dementia screening rate, long-term care workers, and higher home-care service usage rate in long-term care, inhabitants educated about dementia. Conclusions Some clusters of AD deaths were identified, and they were influenced by institutional factors. It is necessary that the local government considers characteristics of each region when implementing the dementia policies. Key messages AD deaths in South Korea were increasing from 2009 to 2018, and their clusters were observed in southern regions. AD deaths in 2018 were influenced by dementia-related policies.

Spatiotemporal distribution and determinants of delayed first antenatal care visit among reproductive age women in Ethiopia: a spatial and multilevel analysis

BackgroundAntenatal care (ANC) is one of the four pillars of the initiative for safe motherhood. ANC helps to improve the health of pregnant women and reduce the risk of adverse pregnancy outcome. First ANC is used to know the health status of the mothers and the fetus, to estimate the gestational age and expected date of delivery. Our research aims to investigate the Spatio-temporal distribution of delayed first ANC visit and its predictors using multilevel binary logistic regression analysis.MethodA total of 10,184 women (2061 in 2005, 3366 in 2011, and 4757 in 2016) were included for this study. The data were cleaned and weighted using STATA version 14. A multilevel binary logistic regression model was fitted to identify significant predictors of delayed first ANC visit. ArcGIS software was used to explore the spatial distribution of delayed first ANC visits and a Bernoulli model was fitted using SaTScan software to identify significant clusters of delayed first ANC visits.ResultsOverall, 77.69, 73.95, and 67.61% of women had delayed their first ANC visit in 2005, 2011, and 2016 EDHSs respectively. Women education [AOR = 0.71; 95%CI; 0.60, 0.84], unwanted pregnancy [AOR = 1.41;95%CI; 1.04, 1.89], and rural residence [AOR = 1.68;95%CI; 1.19, 2.38] have significantly associated with delayed first ANC visit. The spatial analysis revealed that delayed first ANC visit varies in each EDHS period. The SaTScan analysis result of EDHS 2005 data identified 122 primary clusters located between the border of Oromia and Eastern SNNPR regions (RR = 1.30, LLR = 32.31, P-value< 0.001), whereas in 2011 EDHS, 145 primary clusters were identified in entire Tigray, B/Gumuz, Amhara western part of Afar and northwest Oromia regions (RR = 1.30, LLR = 40.79, P-value< 0.001). Besides in 2016 EDHS,198 primary clusters were located in the entire SNNPR, Gambella, Northen B/Gumuz, and western Oromia regions. (RR = 1.35, LLR = 83.21, P-value< 0.001).ConclusionIn Ethiopia delayed first ANC visit was significantly varied across the country over time Women’s education, wanted the last child, and residence were significantly associated with delayed first ANC booking. The effect of each predictor was found to be different across regions of Ethiopia. Therefore, a targeted intervention program is required in highly affected areas of Ethiopia.

Spatial Variation of Child Stunting and Maternal Malnutrition after Controlling for Known Risk Factors in a Drought-Prone Rural Community in Southern Ethiopia.

Background:Globally, understanding spatial analysis of malnutrition is increasingly recognized. However, our knowledge on spatial clustering of malnutrition after controlling for known risk factors of malnutrition such as wealth status, food insecurity, altitude and maternal characteristics is limited from Ethiopia. Previous studies from southern Ethiopia have shown seasonal patterns of malnutrition, yet they did not evaluate spatial clustering of malnutrition.Objective:The aim of this study was to assess whether child stunting and maternal malnutrition were spatially clustered in drought-prone areas after controlling for previously known risk factors of malnutrition.Methods:We used a community-based cohort study design for a one-year study period. We used SaTScan software to identify high rates of child stunting and maternal malnutrition clustering. The outcome based was the presence or absence of stunting and maternal malnutrition ([BMI] <18.5 kg/m2). We controlled for previously known predictors of child stunting and maternal malnutrition to evaluate the presence of clustering. We did a logistic regression model with declaring data to be time-series using Stata version 15 for further evaluation of the predictors of spatial clustering.Results:The crude analysis of SaTScan showed that there were areas (clusters) with a higher risk of stunting and maternal malnutrition than in the underlying at risk populations. Stunted children within an identified spatial cluster were more likely to be from poor households, had younger and illiterate mothers, and often the mothers were farmers and housewives. Children identified within the most likely clusters were 1.6 times more at risk of stunting in the unadjusted analysis. Similarly, mothers within the clusters were 2.4 times more at risk of malnutrition in the unadjusted analysis. However, after adjusting for known risk factors such as wealth status, household food insecurity, altitude, maternal age, maternal education, and maternal occupation with SaTScan analysis, we show that child stunting and maternal malnutrition were not spatially clustered.Conclusion:The observed spatial clustering of child stunting and maternal malnutrition before controlling for known risk factors for child stunting and maternal malnutrition could be due to non-random distribution of risk factors such as poverty and maternal characteristics. Moreover, our results indicated the need for geographically targeted nutritional interventions in a drought-prone area.

Detection of COVID-19 case clusters in Qu\xe9bec, May\u2013October 2020

ObjectivesThe Quebec Public Health Institute (INSPQ) was mandated to develop an automated tool for detecting space-time COVID-19 case clusters to assist regional public health authorities in identifying situations that require public health interventions. This article aims to describe the methodology used and to document the main outcomes achieved.MethodsNew COVID-19 cases are supplied by the “Trajectoire de santé publique” information system, geolocated to civic addresses and then aggregated by day and dissemination area. To target community-level clusters, cases identified as residents of congregate living settings are excluded from the cluster detection analysis. Detection is performed using the space-time scan statistic and Poisson statistical model, and implemented in the SaTScan software. Information on detected clusters is disseminated daily via an online interactive mapping interface.ResultsThe number of clusters detected tracked with the number of new cases. Slightly more than 4900 statistically significant (p ≤ 0.01) space-time clusters were detected over 14 health regions from May to October 2020. The Montréal region was the most affected.ConclusionConsidering the objective of timely cluster detection, the use of near-real-time health surveillance data of varying quality over time and by region constitutes an acceptable compromise between timeliness and data quality. This tool serves to supplement the epidemiologic investigations carried out by regional public health authorities for purposes of COVID-19 management and prevention.

Spatial distribution of traditional male circumcision and associated factors in Ethiopia; using multilevel generalized linear mixed effects model

BackgroundTraditional male circumcision (TMC) is primarily associated with a religious or cultural purpose and may lead to complications. To reduce risks of complication and long-term disabilities that may happen from circumcisions that are undertaken in non-clinical settings, information concerning TMC is very important. Therefore, this study is aimed at identifying spatial distribution of TMC and the factors associated with TMC in Ethiopia.MethodsA secondary data analysis was conducted among 11,209 circumcised males using data from 2016 Ethiopian Demographic and Health Survey (EDHS). Global Moran’s I statistic was observed to check whether there was a significant clustering of TMC. Primary and secondary clusters of TMC were identified by fitting Bernoulli model in Kulldorff’s SaTScan software. Multilevel Generalized Linear Mixed effects Model (GLMM) was fitted to identify factors associated with TMC.ResultThe spatial distribution of TMC was nonrandom across the country with Global Moran’s I = 0.27 (p-value < 0.0001). The primary clusters of TMC were identified in the southern part of Oromia and Tigray, northern part of SNNPR, Amhara, Gambella and Benishangul regions. Current age, age at circumcision, ethnicity, religion, place of residence, wealth index, media exposure, sex of household head and age of household head were factors associated with TMC in Ethiopia.ConclusionsThe spatial distribution of TMC was varied across the country. This variation might be due to the diversity of culture, ethnicity and religion across the regions. Thus, there is a need to rearrange the regulations on standards of TMC practice, conduct training to familiarize operation technique and general hygiene procedures, and launch cross-referral systems between traditional circumcisers and health workers. While undertaking these public health interventions, due attention should be given to the identified clusters and significant factors.

Predictive Value of Time-Space Clusters for HIV Transmission in Washington State, 2017-2019.

Pillar 4 of the United States' End the HIV Epidemic plan is to respond quickly to HIV outbreaks, but the utility of CDC's tool for identifying HIV outbreaks through time-space cluster detection has not been evaluated. The objective of this evaluation is to quantify the ability of the CDC time-space cluster criterion to predict future HIV diagnoses and to compare it to a space-time permutation statistic implemented in SaTScan software. Washington State from 2017 to 2019. We applied both cluster criteria to incident HIV cases in Washington State to identify clusters. Using a repeated-measures Poisson model, we calculated a rate ratio comparing the 6 months after cluster detection with a baseline rate from 24 to 12 months before the cluster was detected. We also compared the demographics of cases within clusters with all other incident cases. The CDC criteria identified 17 clusters containing 192 cases in the 6 months after cluster detection, corresponding to a rate ratio of 1.25 (95% confidence interval: 0.95 to 1.65) relative to baseline. The time-space permutation statistic identified 5 clusters containing 25 cases with a rate ratio of 2.27 (95% confidence interval: 1.28 to 4.03). Individuals in clusters identified by the new criteria were more likely to be of Hispanic origin (61% vs 20%) and in rural areas (51% vs 12%). The space-time permutation cluster analysis is a promising tool for identification of clusters with the largest growth potential for whom interruption may prove most beneficial.

A spatiotemporal analysis of dengue hemorrhagic fever in Banyumas, Indonesia

Dengue hemorrhagic fever (DHF) is a public health problem in the world and also in Indonesia. One of the districts in Central Java that is still having problems with this disease is Banyumas, Indonesia. The incidence rate (IR) data in 2018 was 2.75 per 100,000 populations and the case fatality rate (CFR) was 3.64%. Spatiotemporal analysis was used to determine local variation, geographic determination of risk zones, and measurement of disease control interventions. Therefore, this study aimed to determine the distribution and grouping of dengue cases based on the spatiotemporal analysis. The design was observational with a cross-sectional spatial analysis. This study was conducted in Banyumas, Indonesia with the analysis unit for dengue fever patients in 2018 using as many as 57 cases. Furthermore, the data analysis used includes overlay, buffering, and clustering with SaTScan and ArcGis software. The results showed that there was a clustering of dengue cases in Banyumas, with one primary and three secondary clusters detected. The primary cluster occurred in March-April 2018, involving four sub-districts in urban areas. It was then concluded that the significantly identified clusters indicate a transmission of dengue fever in the Banyumas area with a radius of three kilometers.

Spatiotemporal distribution of measles in China, 2001-2016

Objective: To understand the spatial-temporal distribution and spatial clusters of measles cases in China. Methods: Measles incidence data was collected from the National Notifiable Disease Reporting System of Chinese Center for Disease Control and Prevention. The global and local spatial autocorrelation analyses were conducted by using software ArcGIS 10.2 and spatial-temporal scan was conducted by using software SaTScan 9.6. Results: A total of 1 012 537 cases of measles were reported in China from 2001 to 2016 and the annual incidence showed a sharp downward trend. There was global spatial clustering of measles cases during 2001-2004, 2005-2008, and 2009-2012, and their Moran's I coefficients were 0.29, 0.26, and 0.31, respectively. The results of local spatial autocorrelation analysis showed that there were high- high clustering areas of measles at all time periods, especially in western China. Guangdong province was detected as a separate high-low scattered area from 2005 to 2008 and no low-low clustering area was detected. The spatial-temporal scan statistics showed that there was a wide clustering area covering western, central and northern China, and Shanxi province and Guangxi Zhuang Autonomous Region from 2001-2008. Conclusion: The incidence of measles in China has a certain clustering in both space and time during 2001-2016, the results provide evidence for the development of future strategy of measles prevention and control in China.

Spatial pattern and associated factors of HIV testing and counselling among youths (15\u201324\u2009years) in Ethiopia

BackgroundHIV testing and counseling (HTC) services are key for HIV prevention, treatment, care, and support. Although the prevalence of HIV infection is high among adolescents and young adults, evidence suggests the utilization of HTC service among youth is very low in Ethiopia. Identifying factors and the geographic variation of HTC uptake is important to prioritize and design targeted prevention programs to increase its utilization and reduce HIV infection in hot spot areas.MethodsData from the 2016 Ethiopian Demographic and Health Survey were used to analyze 10,781 youth aged 15–24 years. The spatial analysis was performed in ArcGIS 10.1. The Bernoulli model was used by applying Kulldorff methods using the SaTScan software to analyze the purely spatial clusters of HTC uptake. A multilevel logistic regression analysis was used to identify the associated individual and community-level factors of HTC uptake and estimate between community variance. All models were fitted in Stata version 14.0 and finally, the adjusted odds ratio (AOR) with a corresponding 95% confidence interval (CI) were reported.ResultsIn this study, the spatial patterns of HTC uptake were found to be non-random (Global Moran’s I = 0.074, p value< 0.001). Forty-seven primary clusters were identified that were located in the entire Somali region with a relative likelihood of 1.50 and the Log-Likelihood Ratio of 135.57. Youth who were ever married (AOR = 4.65; 95% CI; 4.05, 5.34), those attended higher education (AOR = 3.97; 95% CI; 3.10,5.08), those from richest household (AOR = 1.86; 95% CI; 1.44, 2.39), aged 20–24 years (AOR = 2.25; 95% CI; 2.02,2.51), having compressive HIV related knowledge (AOR = 2.05; 95% CI; 1.75,2.41), and exposed to media (AOR = 1.38; 95% CI; 1.22,1.57) were positive association with HTC uptake. However, being male (AOR = 0.81; 95% CI; 0.73,0.91) and having high HIV related stigma (AOR = 0.53; 95% CI; 0.42,0.67) were negatively associated with HTC uptake. At the community-level, youth from communities with a high percentage of educated (AOR = 1.45; 95% CI; 1.17,1.80) were more likely to utilize HTC compared with those from communities with low percentages of educated.ConclusionThe current study indicated differences in HTC uptake in the country. Both individual and community-level factors affected HTC uptake in Ethiopia. Multifaceted intervention approaches that consider individual and community factors are required to improve HTC uptake.

Spatial and Temporal Patterns of Plasmodium knowlesi Malaria in Sarawak from 2008 to 2017.

Zoonotic knowlesi malaria has replaced human malaria as the most prevalent malaria disease in Malaysia. The persistence of knowlesi malaria in high-risk transmission areas or hotspots can be discouraging to existing malaria elimination efforts. In this study, retrospective data of laboratory-confirmed knowlesi malaria cases were obtained from the Sarawak Health Department to investigate the spatiotemporal patterns and clustering of knowlesi malaria in the state of Sarawak from 2008 to 2017. Purely spatial, purely temporal, and spatiotemporal analyses were performed using SaTScan software to define clustering of knowlesi malaria incidence. Purely spatial and spatiotemporal analyses indicated most likely clusters of knowlesi malaria in the northern region of Sarawak, along the Sarawak-Kalimantan border, and the inner central region of Sarawak between 2008 and 2017. Temporal cluster was detected between September 2016 and December 2017. This study provides evidence of the existence of statistically significant Plasmodium knowlesi malaria clusters in Sarawak, Malaysia. The analysis approach applied in this study showed potential in establishing surveillance and risk management system for knowlesi malaria control as Malaysia approaches human malaria elimination.

Spatiotemporal distribution of syphilis cases in Wenzhou, 2016–2019

Objective To analyze the spatiotemporal distribution of syphilis cases in Wenzhou from 2016 to 2019 and provide evidence for prevention and control of syphilis. Methods Using software ArcGIS 10.2 as a platform for data management and presentation, a syphilis spatial distribution database in Wenzhou from 2016 to 2019 was established, and spatial autocorrelation analysis was performed based on the incidence of syphilis in Wenzhou during this period. Software SaTScan 9.6 was used for spatiotemporal scanning analysis. Results From 2016 to 2019, a total of 13 778 syphilis cases were reported in Wenzhou, in which 13 550 were included in this analysis. The average annual incidence rate was 37.13/100 000 (range: 0–365.14/100 000). The results of global spatial autocorrelation analysis indicated that the distribution of syphilis cases showed clustering. The result of local Moran’s I autocorrelation analysis found 4 high-high clustering areas, covering 18 townships, in southern Wenzhou. Result from the Getis-Ord General G spatial autocorrelation analysis showed 31 “positive hot spots” and 5 “negative hot spots”. Using software SaTScan 9.6, results from the Phased spatial-temporal analysis identified 7 clustering areas. Conclusion From 2016 to 2019, the incidence of syphilis in Wenzhou was not randomly distributed but showed temporal-spatial clustering. It is necessary to take targeted syphilis prevention and control measures in areas at high risk.

Intra-urban differentials of congenital and acquired syphilis and syphilis in pregnant women in an urban area in northeastern Brazil.

BackgroundCurrently syphilis is considered an epidemic disease worldwide. The objective of this study was to identify intra-urban differentials in the occurrence of congenital and acquired syphilis and syphilis in pregnant women in the city of Natal, in northeast Brazil.MethodsCases of syphilis recorded by the municipal surveillance system from 1 January 2011 to 30 December 2018 were analysed. Spatial statistical analyses were performed using the kernel density estimator of the quadratic smoothing function (weighted). SaTScan software was applied for the calculation of risk based on a discrete Poisson model.ResultsThere were 2163 cases of acquired syphilis, 738 cases of syphilis in pregnant women and 1279 cases of congenital syphilis. Kernel density maps showed that the occurrence of cases is more prevalent in peripheral areas and in areas with more precarious urban infrastructure. In 2011–2014 and 2015–2018, seven statistically significant clusters of acquired syphilis were identified. From 2011 to 2014, the most likely cluster had a relative risk of 3.54 (log likelihood ratio [LLR] 38 895; p<0.001) and from 2015 to 2018 the relative risk was 0.54 (LLR 69 955; p<0.001).ConclusionsIn the municipality of Natal, there was a clustered pattern of spatial distribution of syphilis, with some areas presenting greater risk for the occurrence of new cases.

Spatial distribution, prevalence, and determinants of unintended pregnancy among youth (15-24) in Ethiopia: Further analysis of Ethiopia Demographic and Health Survey.

Objectives:This study aimed to determine the spatial distribution, prevalence, and determinant factors of unintended pregnancy among youth in Ethiopia.Methods:Using the Ethiopian Demographic and Health Survey 2016, a total of 2446 pregnant women aged 15–24 in the last 5 years, including current pregnancy, were included in the study. The unintended pregnancy data were spatially visualized using coordinates for each respondent in the survey using ArcGIS 10.3. The Bernoulli model was used to identify the presence of purely spatial unintended pregnancy cluster using SaTScan software. Logistic regression analysis was fitted to determine factors associated with unintended pregnancy among youth.Results:Unintended pregnancy among youth had spatial variation across the country. Among youth, 20.5% (confidence interval: (19.0, 22.2)) of pregnancies were estimated to be unintended. Spatial scan statistics identified 72 primary clusters (log-likelihood ratio of 37.6, at p < 0.001) which were located in Addis Ababa, southern part of Amhara, northwest of Oromia and northeast of Southern Nations, Nationalities and Peoples Region. Age, region, marital status, occupation, sex of household head, and number of household members were the determinant factors of unintended pregnancy among youth in Ethiopia.Conclusion:The distribution of unintended pregnancy among youth in Ethiopia was nonrandom. Unintended pregnancy prevention strategies among youth need to be targeted on the identified factors. Hence, we recommend creating awareness on sexual and reproductive health rights with special priority to the identified hotspot areas (Amhara, Addis Ababa, Gambella, Northern part of Southern Nations, Nationalities and Peoples Region, and northwest of Oromia region) to reduce unintended pregnancy.