Scan Statistic Research Articles

Neospora caninum antibodies in bulk tank milk from dairy cattle herds in Italy in relation to reproductive and productive parameters and spatial analysis

Among the available diagnostic techniques, antibody detection in bulk tank milk (BTM) represents a useful tool to estimate and monitor Neospora caninum herd prevalence.To evaluate the prevalence of N. caninum and the effect of parasite infection on herd performances, BTM samples collected from 586 dairy herds located in one of the largest dairy production areas in Italy (Lombardy) were analyzed by an indirect ELISA to detect anti-N. caninum specific antibodies. Generalized linear models (GLMs) were developed. A purely spatial analysis scanning for clusters with high or low rates for N. caninum using the Bernoulli model was performed. A maximum entropy approach was used to estimate the probability of distribution of the parasite based on occurrence records together with environmental variables.Overall, 180 herds resulted positive for N. caninum antibodies on bulk tank milk (P = 30.7 %). A higher risk of seropositivity was evidenced in the provinces of Milano, Cremona, Brescia, and Bergamo (P = 32–40 %); a lower risk was evidenced in Lodi, Pavia, and Mantova (P = 13–24 %). A higher risk of seropositivity was revealed for small-medium farms (101–300 animals) (O.R.=2.8) and for older animals with more than 4 years (O.R.=4.4).Regarding the effect of N. caninum infection on herd performances, the number of inseminations for conception was higher (> 3 inseminations), and the period from calving to conception was longer (> 150 days) for positive farms (O.R.=2.0 and O.R.=2.3, respectively); besides, lower head daily milk production (<20 kg and 21–25 kg) and mature equivalent milk yield (<11,000), and somatic cell counts higher than 300,000 cells/ml were observed for N. caninum positive herds (O.R.=0.4, O.R.=0.4 and O.R.=1.9 respectively).The geographical distribution of N. caninum positive farms with the highest level of probability covers the central sector of the Po Plain where a significant cluster for high risk of parasite infection was shown by spatial scan statistic and Maximum entropy ecological niche modelling. A further significant cluster of low risk occurred in the southern. The climatic and environmental variables with the highest training gain when used in isolation resulted altitude, land use/land cover, and other variables related to temperature and precipitation.Neosporosis is widely distributed in Italian dairy herds and an impact of the parasite on herd performances could be hypothesized. Even if the role of N. caninum in alterations of reproductive and productive parameters should be further explored, veterinarians and farmers should be aware of neosporosis, and control plans should be adopted.

An Application of Scan Statistics in Identification and Analysis of Hotspot of Crime against Women in Rajasthan, India

An Application of Scan Statistics in Identification and Analysis of Hotspot of Crime against Women in Rajasthan, India

An open-source implementation of tree-based scan statistics.

We develop an open-source R package to implement tree-based scan statistics (TBSS) analyses. TBSS are data mining methods used by the United States Food and Drug Administration and the Centers for Disease Control. They simultaneously screen thousands of hierarchically aggregated outcomes to identify unsuspected adverse effects of drugs or vaccines, accounting for multiple comparisons. The general structure of TBSS is highly adaptable, with four essential components: (1) a hierarchical outcome structure, (2) a test statistic to be computed for each element of the hierarchy, (3) an algorithm to generate data replicates under a null distribution, and (4) observed outcomes at the lower level of the hierarchy. We encode the general TBSS framework in a convenient R package that offers user-friendly functions for the most used TBSS methods. To illustrate the performance of our software, we evaluated two examples of archetypical TBSS analyses previously analyzed using proprietary, closed-source TreeScan™ software. The first considers the risk of congenital malformations associated with first-trimester exposure to valproate, and the second compares exposure to newly prescribed canagliflozin with a dipeptidyl peptidase 4 inhibitor in adults affected by type 2 diabetes. The results of the original studies are replicated. The diffusion of an open-source implementation of TBSS can enhance innovation of TBSS methods and foster collaborations. We offer an intuitive R package implementing standard TBSS methods with accompanying tutorials. Our unified object-oriented implementation allows expert users to extend the framework, introduce new features, or enhance existing ones.

Spatial variations and determinants of iron containing foods consumption among 6–23 months old children in Ethiopia: spatial, and multilevel analysis

Consuming foods high in iron benefits metabolic processes as well as the development of the neonatal and fetal brain. Despite the significance of eating foods high in iron for public health, Ethiopian practices are still limited when compared to the World Health Organization's (WHO) assessment of its consumption of such foods. This study used the Ethiopia Demographic and Health Survey (EDHS) to evaluate the consumption of iron-rich foods, regional clustering, and related characteristics among children aged 6–23 months. The information was taken from the typical EDHS 2019 dataset, which included a weighted sample of 1572 young children aged 6–23 months old in total. Utilizing Kuldorff's SaTScan version 9.6 software, spatial scan statistics were produced. Software from ArcGIS 10.8 was used to display the regional distribution of inadequate consumption of foods high in iron. Utilizing multilevel or mixed effects logistic regression analysis, the associated determinants for a healthy diet rich in foods containing iron were found. In the final model, a P-value of < 0.05 was announced as a statistical significance variable. Overall, in Ethiopia, children aged 6–23 months consumed iron-rich foods at a rate of 27.14% (95% CI 24.99–29.39). Poor intake of foods heavy in iron is concentrated in Ethiopia's regional states of Afar, a sizable portion of Amhara, Oromia, Tigray, Somali, Gambela, and SNNPS. Primary and secondary education (AOR = 1.73, CI 95%: 1.23, 2.41), and (AOR = 1.97,CI 95%: 1.25, 3.10), having ≥ 2 under five children, and current status of breastfeeding (AOR = 0.62 (CI 95%: 0.45, 0.84), and (AOR = 0.32, CI 95%: 0.23, 0.44), giving birth at health facilities (AOR = 1.51, CI 95%: 1.06, 2.13),being from Afar and Somali regions (AOR = 0.39, 95%: 0.17, 0.93), and (AOR = 0.26, CI 95%: 0.10, 0.69) have shown statistically significant association with the outcome variable respectively. In Ethiopia, providing high-iron meals and supplements to under-2-year-old children represents minimal, but persistent, public health expenses. Based on the identified determinants, the Ethiopian federal ministry of health and other stakeholders should pay special attention to the locations designated as hot spots for maternal and child health service enhancement to promote the consumption of iron-rich meals among children aged 6–23 months.

Space-time analysis of the relationship between landslides occurrence, rainfall variability and ENSO in the Tropical Andean Mountain region in Colombia

According to studies by the Intergovernmental Panel on Climate Change (IPCC), tropical mountainous areas are experiencing increasingly unfavorable climatic conditions regarding geohazards due to a heightened occurrence of intense rainfall events. These climatic shifts contribute to heightened geological risks, notably an elevated frequency of landslides, exacerbating the challenges faced by these regions. There is an urgent need to understand and measure how rainfall variability affects geo-hydrological hazards, which remain difficult to determine and predict. The complex and non-linear space-time relationships and dynamics of rainfall, El Niño-Southern Oscillation (ENSO), and landslides in the Tropical Andean Mountain region in Colombia require an adequate analysis and understanding of their link in terms of its spatial and temporal component at different scales. By evaluation in annual, seasonal, and monthly scales, additional insights on the relationships using a wavelet spectral analysis and a space-time permutation scan statistics method using SaTScan™ are provided. In this study, a space-time and frequency analysis of landslides using a 42-year (1981–2022) rainfall and Multivariate ENSO Index v2.0 time series is presented. According to the results, landslides closely aligned with rainfall patterns, exhibiting a bimodal annual cycle. The ENSO added complexity, with La Niña years leading to more frequent landslides throughout the year and El Niño years showing concentrated occurrences in specific months. This study highlights the influence of rainfall patterns and antecedent rainfall on landslide occurrence, the impact of ENSO phases on rainfall and landslides, and the increasing trend of landslides in Colombia.

Spatial and temporal patterns of haemorrhagic fever with renal syndrome (HFRS) and the impact of environmental drivers in a border area of the Russian Far East.

Haemorrhagic fever with renal syndrome (HFRS) is a significant zoonotic disease transmitted by rodents. The distribution of HFRS in the European part of Russia has been studied quite well; however, much less is known about the endemic area in the Russian Far East. The mutual influence of the epidemic situation in the border regions and the possibility of cross-border transmission of infection remain poorly understood. This study aims to identify the spatiotemporal hot spots of the incidence and the impact of environmental drivers on the HFRS distribution in the Russian Far East. A two-scale study design was performed. Kulldorf's spatial scan statistic was used to conduct spatiotemporal analysis at a regional scale from 2000 to 2020. In addition, an ecological niche model based on maximum entropy was applied to analyse the contribution of various factors and identify spatial favourability at the local scale. One spatiotemporal cluster that existed from 2002 to 2011 and located in the border area and one pure temporal cluster from 2004 to 2007 were revealed. The best suitability for orthohantavirus persistence was found along rivers, including those at the Chinese-Russian border, and was mainly explained by land cover, NDVI (as an indicator of vegetation density and greenness) and elevation. Despite the stable incidence in recent years in, targeted prevention strategies are still needed due to the high potential for HRFS distribution in the southeast of the Russian Far East.

Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders

BackgroundGeographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas.MethodsWe constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters.ResultsWe show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients.ConclusionsOur results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots.

Evidence of spatial clustering of childhood acute lymphoblastic leukemia cases in Greater Mexico City: report from the Mexican Inter-Institutional Group for the identification of the causes of childhood leukemia.

A heterogeneous geographic distribution of childhood acute lymphoblastic leukemia (ALL) cases has been described, possibly, related to the presence of different environmental factors. The aim of the present study was to explore the geographical distribution of childhood ALL cases in Greater Mexico City (GMC). A population-based case-control study was conducted. Children <18 years old, newly diagnosed with ALL and residents of GMC were included. Controls were patients without leukemia recruited from second-level public hospitals, frequency-matched by sex, age, and health institution with the cases. The residence address where the patients lived during the last year before diagnosis (cases) or the interview (controls) was used for geolocation. Kulldorff's spatial scan statistic was used to detect spatial clusters (SCs). Relative risks (RR), associated p-value and number of cases included for each cluster were obtained. A total of 1054 cases with ALL were analyzed. Of these, 408 (38.7%) were distributed across eight SCs detected. A relative risk of 1.61 (p<0.0001) was observed for the main cluster. Similar results were noted for the remaining seven ones. Additionally, a proximity between SCs, electrical installations and petrochemical facilities was observed. The identification of SCs in certain regions of GMC suggest the possible role of environmental factors in the etiology of childhood ALL.

Spatiotemporal pattern of leprosy in southwest China from 2010 to 2020: an ecological study

BackgroundDespite many efforts to control leprosy worldwide, it is still a significant public health problem in low- and middle-income regions. It has been endemic in China for thousands of years, and southwest China has the highest leprosy burden in the country.MethodsThis observational study was conducted with all newly detected leprosy cases in southwest China from 2010 to 2020. Data were extracted from the Leprosy Management Information System (LEPMIS) database in China. The Joinpoint model was used to determine the time trends in the study area. Spatial autocorrelation statistics was performed to understand spatial distribution of leprosy cases. Spatial scan statistics was applied to identify significant clusters with high rate.ResultsA total of 4801 newly detected leprosy cases were reported in southwest China over 11 years. The temporal trends declined stably. The new case detection rate (NCDR) dropped from 4.38/1,000,000 population in 2010 to 1.25/1,000,000 population in 2020, with an average decrease of 12.24% (95% CI: −14.0 to − 10.5; P < 0.001). Results of global spatial autocorrelation showed that leprosy cases presented clustering distribution in the study area. Most likely clusters were identified during the study period and were frequently located at Yunnan or the border areas between Yunnan and Guizhou Provinces. Secondary clusters were always located in the western counties, the border areas between Yunnan and Sichuan Provinces.ConclusionsGeographic regions characterized by clusters with high rates were considered as leprosy high-risk areas. The findings of this study could be used to design leprosy control measures and provide indications to strengthen the surveillance of high-risk areas. These areas should be prioritized in the allocation of resources.

Spatial and spatio-temporal clusters of lung cancer incidence by stage of disease in Michigan, United States 1985-2018.

Lung cancer is the most common cause of cancer-related death in Michigan. Most patients are diagnosed at advanced stages of the disease. There is a need to detect clusters of lung cancer incidence over time, to generate new hypotheses about causation and identify high-risk areas for screening and treatment. The Michigan Cancer Surveillance database of individual lung cancer cases, 1985 to 2018 was used for this study. Spatial and spatiotemporal clusters of lung cancer and level of disease (localized, regional and distant) were detected using discrete Poisson spatial scan statistics at the zip code level over the study time period. The approach detected cancer clusters in cities such as Battle Creek, Sterling Heights and St. Clair County that occurred prior to year 2000 but not afterwards. In the northern area of the lower peninsula and the upper peninsula clusters of late-stage lung cancer emerged after year 2000. In Otter Lake Township and southwest Detroit, late-stage lung cancer clusters persisted. Public and patient education about lung cancer screening programs must remain a health priority in order to optimize lung cancer surveillance. Interventions should also involve programs such as telemedicine to reduce advanced stage disease in remote areas. In cities such as Detroit, residents often live near industry that emits air pollutants. Future research should therefore, continue to focus on the geography of lung cancer to uncover place-based risks and in response, the need for screening and health care services.

Epidemiological and spatial-temporal clustering characteristics of pertussis in Hebei Province from 2013 to 2022

Objective: To analyze the spatial-temporal epidemiological characteristics of pertussis from 2013 to 2022 in Hebei Province and to provide a reference for improving prevention and control measures. Methods: Based on the data of pertussis reported in Hebei Province during 2013-2022 to analyze the popular characteristic, the ArcGIS 10.8 software was used to construct a ring map and to perform spatial autocorrelation analysis; the SaTScan 10.1 software was used for spatial-temporal scan statistics. Results: There were 6 715 cases of the cumulative report in Hebei Province from 2013 to 2022 without death. The annual report incidence was 0.90/100 000. The overall incidence rate showed an upward trend from 2013 to 2019, and during 2020-2021, it showed a sharp decline, but in 2022, it showed a sharp increase. Summer and autumn are the peak seasons of the epidemic. The incidence was highest in age group <1 year (48.67%), and the lowest age group in age group ≥15 years (0.45%) and mainly scattered children (78.03%); the incidence about men is higher than women. Spatial autocorrelation analysis showed that the onset of pertussis has spatial clustering, and high-high clusters were found in Langfang, Baoding, and Cangzhou, the top three countries with reported incidence. The area covered by a low-low cluster was consistent with the distribution of the corresponding low-incidence areas in this study. Space-time scan detects five statistically significant areas, and three zones were concentrated in 2022. Conclusions: The incidence of pertussis in Hebei had obvious season, population, and area-specific differences. There was obvious spatiotemporal and clustering, so the control of key areas should target the characteristics of time and space.

Impact of the COVID-19 Pandemic Surveillance of Visceral Leishmaniasis in Brazil: An Ecological Study.

The aim of the study was to assess the impact of the COVID-19 pandemic on the notification of new VL cases in Brazil in 2020. It is an ecological and time-series study (2015-2020) with spatial analysis techniques, whose units of analysis were the 5570 Brazilian municipalities. The study population consisted of all new cases of VL recorded between 2015 and 2020. The P-score was calculated to estimate the percentage variation in new VL cases. Global and local univariate Moran's Indices and retrospective space-time scan statistics were used in spatial and space-time analyses, respectively. It was expected that there would be 3627 new cases of VL in Brazil in 2020, but 1932 cases were reported (-46.73%). All Brazilian regions presented a negative percentage variation in the registration of new VL cases, with the Southeast (-54.70%), North (-49.97%), and Northeast (-44.22%) standing out. There was spatial dependence of the disease nationwide in both periods, before and during the first year of the COVID-19 pandemic. There was a significant reduction in the incidence of new VL cases in Brazil during the first year of the COVID-19 pandemic. These findings reinforce the need for better preparedness of the health system, especially in situations of new epidemics.

Spatial analysis of multivariate factors influencing suicide hotspots in Urban Tamil Nadu

Clusters of suicide occur when there is a concentration of frequent incidents happening closely together in both time and space. Despite advancements in technology, there has been a persistent increase in suicide instances that has proven challenging to effectively manage. This research utilizes longitudinal and spatiotemporal data sourced from reports by the Indian Ministry of Home Affairs and the Tamil Nadu government. The objective is to comprehensively examine the spatial dimension of suicide along with its influencing factors, employing scan statistics for the years 2020 and 2021. Hypothesis testing is conducted to compare hotspot and coldspot locations consistently identified within the study period of 2012-2021. To unravel the underlying causes of suicide within the consistent hotspot zone, a multivariate analysis approach is employed. Notably, this study highlights Madurai, a major city in Tamil Nadu, as a statistically significant and enduring hotspot for suicide. The analysis identifies economic factors as the primary catalyst for the escalating suicide rates in this hotspot region. This emphasizes the urgent need for increased attention to address this issue effectively. State-level assessment of suicide instances and its concerning factors, the restrictive measure of suicide instances due to availability of data sources. This study provides a roadmap that aims to assist health and governmental entities in formulating, strategizing, and implementing feasible preventive measures specifically tailored to curbing suicide incidents in urban Tamil Nadu.

Mosquitoes provide a transmission route between possums and humans for Buruli ulcer in southeastern Australia

Buruli ulcer, a chronic subcutaneous infection caused by Mycobacterium ulcerans, is increasing in prevalence in southeastern Australia. Possums are a local wildlife reservoir for M. ulcerans and, although mosquitoes have been implicated in transmission, it remains unclear how humans acquire infection. We conducted extensive field survey analyses of M. ulcerans prevalence among mosquitoes in the Mornington Peninsula region of southeastern Australia. PCR screening of trapped mosquitoes revealed a significant association between M. ulcerans and Aedes notoscriptus. Spatial scanning statistics revealed overlap between clusters of M. ulcerans-positive Ae. notoscriptus, M. ulcerans-positive possum excreta and Buruli ulcer cases, and metabarcoding analyses showed individual mosquitoes had fed on humans and possums. Bacterial genomic analysis confirmed shared single-nucleotide-polymorphism profiles for M. ulcerans detected in mosquitoes, possum excreta and humans. These findings indicate Ae. notoscriptus probably transmit M. ulcerans in southeastern Australia and highlight mosquito control as a Buruli ulcer prevention measure.

Spatial spillover effect of environmental factors on the tuberculosis occurrence among the elderly: a surveillance analysis for nearly a dozen years in eastern China

BackgroundIn many areas of China, over 30% of tuberculosis cases occur among the elderly. We aimed to investigate the spatial distribution and environmental factors that predicted the occurence of tuberculosis in this group.MethodsData were collected on notified pulmonary tuberculosis (PTB) cases aged ≥ 65 years in Zhejiang Province from 2010 to 2021. We performed spatial autocorrelation and spatial-temporal scan statistics to determine the clusters of epidemics. Spatial Durbin Model (SDM) analysis was used to identify significant environmental factors and their spatial spillover effects.Results77,405 cases of PTB among the elderly were notified, showing a decreasing trend in the notification rate. Spatial-temporal analysis showed clustering of epidemics in the western area of Zhejiang Province. The results of the SDM indicated that a one-unit increase in PM2.5 led to a 0.396% increase in the local notification rate. The annual mean temperature and precipitation had direct effects and spatial spillover effects on the rate, while complexity of the shape of the greenspace (SHAPE_AM) and SO2 had negative spatial spillover effects.ConclusionTargeted interventions among the elderly in Western Zhejiang may be more efficient than broad, province-wide interventions. Low annual mean temperature and high annual mean precipitation in local and neighboring areas tend to have higher PTB onset among the elderly.

Geographic variation of HPV-associated cancer incidence in Kentucky using spatial scan statistics.

Populations with high cancer risk that are targeted for screening, education, and vaccination have been shown to increase rates of screening, which ultimately may improve timing of diagnosis and overall outcome for certain cancers. Spatial scan analysis provides a visual representation of areas with higher rates of disease. Limited research has used this methodology to assess HPV-associated cancers. Using, spatial scan statistics, our goal was to identify regions within Kentucky having significantly higher rates of HPV-associated tumors. These regions can be targeted for public health efforts in the form of education, vaccination, screening, and physician recruitment. The Kentucky Cancer Registry data from 1995 to 2016 and spatial scan statistics were used to identify county-level clusters with high-incidence of HPV-associated cancers after adjustment for age and sex. Anatomic sites included in this analysis were oropharynx, cervix, anus, penis, and vulva. There was one high-rate cluster of oropharyngeal cancer, which was observed in the Louisville metropolitan region (Relative Risk [RR] = 1.24, p < 0.001). One high-rate cluster of anal and penile cancer incidence in men was identified that partially overlapped with the oropharyngeal cluster. There were five clusters of higher cervical, vulvar, and anal cancer incidence in females, one of which overlapped with the oropharyngeal cluster. Overlapping clusters of HPV-associated cancers were identified at the county-level and included both urban and rural counties of Kentucky. Findings can assist in the design of public health interventions to increase screenings, promote vaccination, and recruit physicians in these regions to improve prevention, diagnosis, and early treatment of HPV-associated cancers.

Mortalidade materna no Brasil: análise de tendências temporais e agrupamentos espaciais

Abstract This article aims to analyze spatial and temporal patterns of maternal mortality in Brazil during the period 2010-2020 and identify related socioeconomic indicators. We conducted an ecological study of the maternal mortality ratio (MMR) in Brazil’s municipalities using secondary data. Temporal analysis was performed using the joinpoint method. Bayesian statistics, spatial autocorrelation, the Getis Ord Gi* technique and the scan statistic were used to identify spatial clusters, and multiple non-spatial and spatial regression models were used to assess the association between factors and the MMR. There was an increase in the MMR in 2020 and an increase in deaths in the North and Southeast. Clusters were found in Amazonas, Tocantins, Piauí, Maranhão, Bahia and Mato Grosso do Sul. The following indicators were negatively associated with the MMR: cesarean section rate, Municipal Human Development Index, and per capita household income of people who are vulnerable to poverty. The MMR was stable up to 2019, followed by a sharp rise in 2020 coinciding with the onset of the Covid-19 pandemic in the country. It is essential that efforts to reduce maternal mortality in Brazil extend beyond the promotion of improvements in antenatal, childbirth and postpartum care to address the social determinants of the problem.

Temporal trends and spatial analysis of leprosy surveillance indicators in the municipalities of the state of Mato Grosso, 2008-2022.

In 2022, Mato Grosso (MT, Brazil) reported the highest detection rate of new leprosy cases (66.20 per 100,000 inhabitants) among all Brazilian states. Monitoring of leprosy indicators is an important control strategy in hyperendemic areas. We aimed to describe the temporal trends and identify clusters of municipalities according to leprosy surveillance indicators in MT between 2008 and 2022. Data from the Notifiable Diseases Information System were used to analyze new case detection rate of leprosy (NCDR), new case detection rate of leprosy among children aged <15 years (NCD15), and rate of new cases with grade 2 physical disability (G2DR). Spatial scan statistics with pure spatial analysis and spatial autocorrelation maps were used to analyze the spatial patterns. Joinpoint regression was used to estimate the annual percentage change (APC) in these indicators. The NCDR decreased (APC: -20.2%, 95% confidence interval (CI): -38.7% to -7.4%) between 2019 and 2021. The NCD15 also decreased (APC: -19.2%, 95% CI: -36.4% to -10.3%) between 2018 and 2022. Conversely, the G2DR remained stable throughout the study (APC: 3.2%, 95% CI: -0.1% to 6.7%). Global Moran's index (Moran's I) confirmed the existence of spatial dependence among the municipalities for NCDR (Moran's I=0.348), NCD15 (Moran's I=0.269), and G2DR (Moran's I=0.275). Clusters with high NCDR levels included 13 municipalities in the northern and eastern macroregions, while clusters with high G2DR levels included 12 municipalities in the northwestern, northern, and eastern macroregions. The NCDR and NCD15 decreased, but the G2DR remained stable between 2018 and 2022. The coronavirus disease 2019 (COVID-19) pandemic had a potential negative impact on leprosy case detection, highlighting the need to strengthen leprosy surveillance efforts. The identified clusters of MT municipalities can significantly assist in this task.

Exploring Spatial Variation of Women’s Tetanus Vaccination in Ethiopia: Spatial Analysis of Ethiopian Demographic and Health Survey 2016

Tetanus is a bacterial infection that causes painful muscular contractions throughout the body, usually starting in the jaw. Every year, 15,000 to 30,000 maternal deaths occur due to tetanus related to the delivery process. Exploring variations of women’s tetanus immunization is crucial for programmers’ planning and monitoring. As a result, this study aims to evaluate the spatial distribution of women’s tetanus vaccination coverage and risk areas of women’s tetanus vaccination clustering in Ethiopia. The study used Ethiopian Demographic and Health Survey data, which was conducted in 2016 using the Ethiopia Population and Housing Census 2007 sampling frame. From 15,683 women aged 15 to 49, a sample of 7,193 women was selected using eligible criteria. This study used spatial data analysis. To determine geographical danger zones for tetanus vaccination of women, cluster, hotspot analysis, spatial interpolation, and spatial scan statistics were used. At the regional level of Ethiopia, tetanus vaccination was spatially clustered (Global Moran’s I = 0.066, p = .0001). Western Tigray, eastern SNNP, and northern Oromia were identified as hotspots of poor tetanus vaccine coverage, whereas western Oromia, Afar, and southeast Amhara regions were designated as non-risky areas of Ethiopia. The spatial Bayesian kriging interpolation analysis predicted high-risk areas were the southwestern and eastern parts of Oromia, western Tigray, Harari, and Dire Dawa Western Tigray, the eastern SNNP, southern Amhara, and northern Oromia have been recognized as a significant hotspot. Health workers, programmers, government, and non-governmental organizations in Ethiopia will implement spatially based strategic interventions for women’s tetanus immunization.

Hotspot areas of risky sexual behaviour and associated factors in Ethiopia: Further spatial and mixed effect analysis of Ethiopian demographic health survey.

Sexual behaviour needs to take a central position in the heart of public health policy makers and researchers. This is important in view of its association with Sexually Transmitted Infections (STIs), including HIV. Though the prevalence of HIV/AIDS is declining in Ethiopia, the country is still one of the hardest hit in the continent of Africa. Hence, this study was aimed at identifying hot spot areas and associated factors of risky sexual behavior (RSB). This would be vital for more targeted interventions which can produce a sexually healthy community in Ethiopia. In this study, a cross-sectional survey study design was employed. A further analysis of the 2016 Ethiopia Demographic and Health Survey data was done on a total weighted sample of 10,518 women and men age 15-49 years. ArcGIS version 10.7 and Kuldorff's SaTScan version 9.6 software were used for spatial analysis. Global Moran's I statistic was employed to test the spatial autocorrelation, and Getis-Ord Gi* as well as Bernoulli-based purely spatial scan statistics were used to detect significant spatial clusters of RSB. Mixed effect multivariable logistic regression model was fitted to identify predictors and variables with a p-value ≤0.05 were considered as statistically significant. The study subjects who had RSB were found to account about 10.2% (95% CI: 9.64%, 10.81%) of the population, and spatial clustering of RSB was observed (Moran's I = 0.82, p-value = 0.001). Significant hot spot areas of RSB were observed in Gambela, Addis Ababa and Dire Dawa. The primary and secondary SaTScan clusters were detected in Addis Ababa (RR = 3.26, LLR = 111.59, P<0.01), and almost the entire Gambela (RR = 2.95, LLR = 56.45, P<0.01) respectively. Age, literacy level, smoking status, ever heard of HIV/AIDS, residence and region were found to be significant predictors of RSB. In this study, spatial clustering of risky sexual behaviour was observed in Ethiopia, and hot spot clusters were detected in Addis Ababa, Dire Dawa and Gambela regions. Therefore, interventions which can mitigate RSB should be designed and implemented in the identified hot spot areas of Ethiopia. Interventions targeting the identified factors could be helpful in controlling the problem.