Severe weather events and cryptosporidiosis in Aotearoa New Zealand: A case series of space-time clusters.

Occurrence of cryptosporidiosis has been associated with weather conditions in many settings internationally. We explored statistical clusters of human cryptosporidiosis and their relationship with severe weather events in New Zealand (NZ). Notified cases of cryptosporidiosis from 1997 to 2015 were obtained from the national surveillance system. Retrospective space-time permutation was used to identify statistical clusters. Cluster data were compared to severe weather events in a national database. SaTScan analysis detected 38 statistically significant cryptosporidiosis clusters. Around a third (34.2%, 13/38) of these clusters showed temporal and spatial alignment with severe weather events. Of these, nearly half (46.2%, 6/13) occurred in the spring. Only five (38%, 5/13) of these clusters corresponded to a previously reported cryptosporidiosis outbreak. This study provides additional evidence that severe weather events may contribute to the development of some cryptosporidiosis clusters. Further research on this association is needed as rainfall intensity is projected to rise in NZ due to climate change. The findings also provide further arguments for upgrading the quality of drinking water sources to minimize contamination with pathogens from runoff from livestock agriculture.

Space-time clustering of COVID-19 cases in the United States veteran population.

PURPOSE: To assess the distribution and clustering of coronavirus disease 2019 (COVID-19) testing and incidence over space and time, U.S. Department of Veteran's Affairs (VA) data were used to describe where and when veterans experienced highest proportions of test positivity. METHODS: Data for 6,342,455 veterans who utilized VA services between January 1, 2018, and September 30, 2021, were assessed for COVID-19 testing and test positivity. Testing and positivity proportions by county were mapped and focused-cluster tests identified significant clustering around VA facilities. Spatial cluster analysis also identified where and when veterans experienced highest proportions of test positivity. RESULTS: Within the veterans study population and our time window, 21.3% received at least one COVID-19 test, and 20.4% of those tested had at least one positive test. There was statistically significant clustering of testing around VA facilities, revealing regional variation in testing practices. Veterans experienced highest test positivity proportions between November 2020 and January 2021 in a cluster of states in the Midwest, compared to those who received testing outside of the identified cluster (RR: 3.45). CONCLUSIONS: Findings reflect broad regional trends in COVID-19 positivity which can inform VA policy and resource allocation. Additional analysis is needed to understand patterns during Delta and Omicron variant periods.

Spatiotemporal and seasonality analysis of sheep and goat pox (SGP) disease outbreaks in Turkey between 2010 and 2019.

Sheep and goat pox (SGP) is a highly infectious disease with a high case fatality rate. It causes serious economic losses and decreases productivity in infected facilities and contact areas. As in many countries of the world, SGP outbreaks reported from Turkey to the World Organization for Animal Health (OIE) continue to threaten animal health. Therefore, studies that will guide the production of effective policies to prevent and control SGP are extremely important. This study aims at evaluating the spatiotemporal distribution of SGP outbreaks by geographical information system (GIS)-based analyses. In accordance with this purpose, spatiotemporal scan analyses were applied to reveal the spatiotemporal distribution pattern and transmission of SGP outbreaks reported in Turkey between 2010 and 2019. Space-time cluster analysis revealed 4 several clusters, indicating geographic areas at the highest risk. Spatiotemporal clusters were 6 to 11 times more likely to be exposed to SGP than the general distribution. The average spatiotemporal density of outbreaks in clusters was estimated as 0.20 ± 0.07 outbreaks per 1000 km2 per month. Seasonal analysis and time series analysis showed similar findings. The seasonality of SGP was mainly defined in the winter (from December to February) when the seasonal adjusted factor (SAF) was at a peak of 504.6. In addition, February had the highest SAF with 7.1. Directional distribution analysis showed that the transmission of SGP was oriented between northeast (NE)-southwest (SW) and northwest (NW)-southeast (SE) and that distribution was changed every 2 years. These findings present a basis for the effective monitoring and prevention of SGP and provide valuable information to policymakers.

Geographical distribution and space-time clustering of human illnesses with major Salmonella serotypes in Florida, USA, 2017-2018.

Nontyphoidal salmonellosis is the leading reported foodborne illness in Florida. Although the diversity of Salmonella serotypes circulating in Florida has been identified, the geographical characteristics of the major serotypes are poorly described. Here we examined the geospatial patterns of 803 whole-genome sequenced Salmonella isolates within seven major serotypes (Enteritidis, Newport, Javiana, Sandiego, Braenderup, Typhimurium and I 4,[5],12:i:-) with the metadata obtained from Florida Department of Health during 2017-2018. Geographically, the distribution of incidence rates varied distinctively between serotypes. Illnesses with Enteritidis and Newport serotypes were widespread in Florida. The incidence rate for Javiana was relatively higher in the north compared to the south. Typhimurium was concentrated in the northwest, while I 4,[5],12:i:-, the monophasic variant of Typhimurium was limited to the south. We also evaluated space-time clustering of isolates at the zip code level using scan statistic models. Space-time clusters were detected for each major serotype during 2017-2018. The multinomial scan statistic found the risk of illness with Javiana was higher in the north and southwest in the fall of 2017 compared to other major serotypes. This serotype-specific clustering analysis will assist in further unpacking the associations between distinct reservoirs and illnesses with major serotypes in Florida.

Preponderance of vaccine-preventable diseases hotspots in northern Ghana: a spatial and space-time clustering analysis from 2010 to 2014.

BACKGROUND: Vaccine-preventable diseases (VPDs) persist globally with a disproportionately high burden in Low and Middle-Income Countries (LMICs). Although this might be partly due to the failure to sustain vaccination coverage above 90% in some WHO regions, a more nuanced understanding of VPD transmission beyond vaccination coverage may unveil other important factors in VPD transmission and control. This study identified VPDs hotspots and explored their relationships with ecology, urbanicity and land-use variations (Artisanal and Small-scale Gold Mining (ASGM) activities) in Ghana. METHODS: District-level disease count data from 2010 to 2014 from the Ghana Health Service (GHS) and population data from the Ghana Population and Housing Census (PHC) were used to determine clustering patterns of six VPDs (Measles, Meningitis, Mumps, Otitis media, Pneumonia and Tetanus). Spatial and space-time cluster analyses were implemented in SaTScan using the discrete Poisson model. P-values were estimated using a combination of sequential Monte Carlo, standard Monte Carlo, and Gumbel approximations. RESULTS: The study found a preponderance for VPD hotspots in the northern parts of Ghana and northernmost ecological zones (Sudan Savannah and Guinea Savannah). Incidence of meningitis was higher in the Sudan Savannah ecological zone relative to: Tropical Rain Forest (p = 0.001); Semi Deciduous Forest (p < 0.0001); Transitional Zone (p < 0.0001); Coastal Savannah (p < 0.0001) and Guinea Savannah (p = 0.033). Except for mumps, which recorded a higher incidence in urban districts (p = 0.045), incidence of the other five VPDs did not differ across the urban-rural divide. Whereas spatial analysis suggested that some VPD hotspots (tetanus and otitis media) occur more frequently in mining districts in the southern part of the country, a Mann-Whitney U test revealed a higher incidence of meningitis in non-mining districts (p = 0.019). Pneumonia and meningitis recorded the highest (722.8 per 100,000) and least (0.8 per 100,000) incidence rates respectively during the study period. CONCLUSION: This study shows a preponderance of VPD hotspots in the northern parts of Ghana and in semi-arid ecoclimates. The relationship between ASGM activities and VPD transmission in Ghana remains blurred and requires further studies with better spatial resolution to clarify.

Clusters of malaria cases at sub-district level in endemic area in Java Island, Indonesia.

Malaria remains one of the essential public health problems in Indonesia. The year 2015 was originally set as the elimination target in Java Island, but there are still several regencies on Java reporting malaria cases. Spatial technology helps determine local variations in malaria transmission, control risk areas and assess the outcome of interventions. Information on distribution patterns of malaria at the sub-district level, presented as spatial, temporal, and spatiotemporal data, is vital in planning control interventions. Information on malaria transmission at the sub-district level in three regencies in Java (Banyumas, Kebumen, and Purbalingga) was collected from the Agency for Regional Development (Bappeda), the Population and Civil Registration Agency (Disdukcapil) and Statistics Indonesia (BPS). Global spatial autocorrelation and space-time clustering was investigated together with purely spatial and purely temporal analyses using geographical information systems (GIS) by ArcGis 10.2 and SaTScan 8.0 to detect areas at high risk of malaria. Our results show that malaria was spatially clustered in the study area in central Java, in particular in the Banyumas and Purbalingga regencies. The temporal analysis revealed that malaria clusters predominantly appeared in the period January-April. The results of the spatiotemporal analysis showed that there was one most likely malaria cluster and three secondary clusters in southern central Java. The most likely cluster was located in Purbalingga Regency covering one sub-district and remaining from the beginning of 2016 to the end of 2018. The approach used can assist the setting of resource priorities to control and eliminate malaria.

Space-time clustering-based method to optimize shareability in real-time ride-sharing.

Real-time ride-sharing has become popular in recent years. However, the underlying optimization problem for this service is highly complex. One of the most critical challenges when solving the problem is solution quality and computation time, especially in large-scale problems where the number of received requests is huge. In this paper, we rely on an exact solving method to ensure the quality of the solution, while using AI-based techniques to limit the number of requests that we feed to the solver. More precisely, we propose a clustering method based on a new shareability function to put the most shareable trips inside separate clusters. Previous studies only consider Spatio-temporal dependencies to do clustering on the mobility service requests, which is not efficient in finding the shareable trips. Here, we define the shareability function to consider all the different sharing states for each pair of trips. Each cluster is then managed with a proposed heuristic framework in order to solve the matching problem inside each cluster. As the method favors sharing, we present the number of sharing constraints to allow the service to choose the number of shared trips. To validate our proposal, we employ the proposed method on the network of Lyon city in France, with half-million requests in the morning peak from 6 to 10 AM. The results demonstrate that the algorithm can provide high-quality solutions in a short time for large-scale problems. The proposed clustering method can also be used for different mobility service problems such as car-sharing, bike-sharing, etc.

Diferencias socioespaciales entre homicidios y suicidios en Argentina, 1994-2014 / Diferenças socioespaciais entre homicídios e suicídios na Argentina, 1994-2014 / Socio-spatial differences between homicide and suicide in Argentina, 1994-2014

Los objetivos de este estudio son descubrir la conformación de conglomerados espaciotemporales de los suicidios, homicidios y muertes por lesiones de intención no determinada (MLIND) en Argentina, durante el período 1994-2014, y analizar la asociación espaciotemporal entre conglomerados de suicidios u homicidios y conglomerados de MLIND en Argentina durante el mismo período. Las unidades espaciales fueron los departamentos de Argentina. Se hizo un rastreo estadístico espaciotemporal para la detección de conglomerados por sexo y grupos de edad (10 a 29, 30 a 59 y 60 o más años). Se utilizaron dos modelos espaciotemporales: multinomial y Bernoulli. La emergencia de conglomerados de homicidios en hombres estuvo más asociada a caídas más abruptas en los niveles de empleo, entre 1991 y 2001, en comparación a los suicidios. Las áreas con densidades poblacionales altas y porcentajes más altos de necesidades básicas insatisfechas (NBI) tendieron a estar incluidas en conglomerados de homicidio en hombres en comparación a los suicidios. Hubo un mayor solapamiento espaciotemporal entre MLIND y homicidios. Los resultados obtenidos apoyan las hipótesis de 1) una diferenciación geográfica entre homicidios y suicidios en tiempos de crisis económica y 2) la representación mayoritaria de MLIND en homicidios ocultos.

Os objetivos deste estudo são: conhecer a conformação dos conglomerados espaço-temporais de suicídios, homicídios e óbitos por lesões por intenção indeterminada (MLIND) na Argentina, durante o período 1994-2014; e analisar a associação espaço-temporal entre grupos de suicídio ou homicídio e grupos de MLIND, na Argentina no mesmo período. As unidades espaciais foram os departamentos da Argentina. Uma varredura estatística espaço-temporal foi realizada para detectar clusters por sexo e grupos de idade (10-29, 30-59 e 60 anos ou mais). Dois modelos espaço-temporais foram usados: multinomial e Bernoulli. O surgimento de conglomerados de homicídios em homens esteve mais associado a reduções mais acentuadas nos níveis de emprego, entre 1991 e 2001, em comparação com os suicídios. Áreas com altas densidades populacionais e maiores percentuais de necessidades básicas insatisfeitas (indicador de pobreza) tenderam a ser incluídas em conglomerados de homicídio em homens, em comparação com suicídios. Houve uma maior sobreposição espaço-temporal entre MLIND e homicídios. Os resultados obtidos suportam as hipóteses de uma diferenciação geográfica entre homicídios e suicídios em tempos de crise económica e que os MLINDs representariam principalmente homicídios ocultos.

The objectives of this study are to discover the conformation of spatio-temporal clusters of suicides, homicides and deaths due to injuries of undetermined intention (MLIND) in Argentina, during the period 1994-2014, and to analyze the spatio-temporal association between suicide or homicide clusters and MLIND clusters in Argentina during the same period. The spatial units were the departments of Argentina. Space-time scan statistics were performed to detect clusters by sex and age groups (10-29 years, 30-59 years and 60 or more years). Two space-time models were used: multinomial and Bernoulli. The emergence of homicide clusters in men was more associated with steeper drops in employment levels, between 1991 and 2001, compared to suicide clusters. Areas with the highest population density and with the highest percentage of Unsatisfied Basic Needs (poverty indicator) were more likely to be included in clusters with high proportions of homicide in men, compared to suicide. There was a greater spatio-temporal overlap between MLIND and homicides. The results obtained support the hypotheses of (1) a geographical differentiation between homicides and suicides in times of economic crisis; and (2) MLIND would represent mostly hidden homicides.

COVID-19 y adultos mayores: comparación espaciotemporal entre mortalidad y vacunación en la provincia de Buenos Aires, Argentina / COVID-19 and older adults: spatiotemporal comparison between mortality and vaccination in the province of Buenos Aires, Argentina

RESUMEN El objetivo de este estudio fue analizar las variaciones espaciotemporales de la mortalidad por COVID-19 en adultos mayores y de la vacunación contra la COVID-19 en esta población. Se utilizaron datos de defunciones por COVID-19 y de personas de 70 a más años inmunizadas con la primera dosis de vacunas contra esta enfermedad, en partidos de la provincia de Buenos Aires, desde el 29 de diciembre del 2020 al 30 de junio de 2021. Se emplearon técnicas de escaneo espaciotemporal para detectar conglomerados. Los partidos del Gran Buenos Aires que tuvieron mayor vacunación con la primera dosis de la vacuna Sputnik V en población de 70 a más años, entre mediados de marzo y principios de abril de 2021, coincidieron mayormente en registrar una disminución de la mortalidad en esta población, entre finales de abril y finales de junio de 2021. Este estudio mostró algunos indicios del impacto positivo de la aplicación de la primera dosis de la vacuna Sputnik V en el Gran Buenos Aires.

ABSTRACT The aim of this study was to analyze the spatiotemporal variations of COVID-19 mortality and vaccination against COVID-19 in older adults. We used data from deaths due to COVID-19 and persons aged 70 years and older immunized with the first dose of vaccines against this disease, from districts of the province of Buenos Aires, between December 29, 2020, and June 30, 2021. Spatiotemporal scanning techniques were used to detect clusters. The parties of Greater Buenos Aires that had the highest vaccination rate with the first dose of the Sputnik V vaccine in population aged 70 years and older, between mid-March and early April 2021, also registered a decrease in mortality in this population, between the end of April and the end of June 2021. This study showed some signs of the positive impact associated with the application of the first dose of Sputnik V vaccine in Greater Buenos Aires.

Two-stage algorithms for visually exploring spatio-temporal clustering of avian influenza virus outbreaks in poultry farms.

The development of visual tools for the timely identification of spatio-temporal clusters will assist in implementing control measures to prevent further damage. From January 2015 to June 2020, a total number of 1463 avian influenza outbreak farms were detected in Taiwan and further confirmed to be affected by highly pathogenic avian influenza subtype H5Nx. In this study, we adopted two common concepts of spatio-temporal clustering methods, the Knox test and scan statistics, with visual tools to explore the dynamic changes of clustering patterns. Since most (68.6%) of the outbreak farms were detected in 2015, only the data from 2015 was used in this study. The first two-stage algorithm performs the Knox test, which established a threshold of 7 days and identified 11 major clusters in the six counties of southwestern Taiwan, followed by the standard deviational ellipse (SDE) method implemented on each cluster to reveal the transmission direction. The second algorithm applies scan likelihood ratio statistics followed by AGC index to visualize the dynamic changes of the local aggregation pattern of disease clusters at the regional level. Compared to the one-stage aggregation approach, Knox-based and AGC mapping were more sensitive in small-scale spatio-temporal clustering.

Spatio-temporal trend of BIRADS classification suggestive of malignancy: a national analysis of mammograms, 2013-2017.

INTRODUCTION: Promoting breast cancer (BC) detection in women by means of mammography is a viable strategy to reduce the number of diagnoses at clinically advanced stages and mortality. OBJECTIVES: To describe the results reported by mammography studies in women, carried out nationally during 2013-2017, and to analyze the spatiotemporal trend of Breast Imaging Reporting and Data System (BIRADS) categories suggestive of malignancy by State. METHOD: Longitudinal, analytical design that included information on mammography studies of women according to age group (< 40 and ≥ 40), evaluated in units of the Ministry of Health of Mexico during 2013-2017. The frequency of BIRADS categories and a standardized rate suggestive of malignancy (categories 4 and 5) were estimated in women aged ≥ 40 years, and spatial statistics were used to analyze the trend by State. RESULTS: A total of 3,659,151 mammograms were analyzed, 98.5 % in women aged ≥ 40 years. The malignancy-suggestive rate decreased from 38.3 (2013) to 31 (2017) per 100,000 women aged ≥ 40 years; however, the risk of detection increased up to 13 times in ten States. CONCLUSIONS: Although the risk of detection in categories suggestive of malignancy decreased at the national level, some States need to reinforce the application of BC detection programs through mammography and increase the participation of the target population.

INTRODUCCIÓN: Promover la detección de cáncer de mama (CaMa) en mujeres mediante mastografía es una estrategia viable para disminuir los diagnósticos en fases clínicamente avanzadas y la mortalidad. OBJETIVOS: Describir los resultados reportados por estudios de mastografía en mujeres realizados a nivel nacional durante 2013-2017 y analizar la tendencia espaciotemporal de categorías BIRADS (Breast Imaging Reporting and Data System) sugestivas de malignidad por Estado. MÉTODO: Diseño analítico longitudinal que incluyó información sobre estudios de mastografía de mujeres según grupo de edad (< 40 e ≥ 40), valoradas en unidades de la Secretaría de Salud, México, durante 2013-2017. Se estimó la frecuencia de categorías según BIRADS, tasa estandarizada sugestiva de malignidad (categorías 4 y 5) en mujeres ≥ 40 años y se utilizó estadística espacial para analizar la tendencia por Estado. RESULTADOS: Se analizaron 3,659,151 mastografías, el 98.5 % en mujeres ≥ 40 años. La tasa sugestiva de malignidad disminuyó de 38.3 (2013) a 31 (2017) por 100 mil mujeres ≥ 40 años; sin embargo, el riesgo de detección aumentó hasta 13 veces en diez Estados. CONCLUSIONES: Aunque el riesgo de detección en categorías sugestivas de malignidad disminuyó a nivel nacional, algunos Estados requieren reforzar la aplicación de programas de detección del CaMa mediante mastografía e incrementar la participación de la población blanco.

Global, regional and national incidence, mortality and disability-adjusted life-years of skin cancers and trend analysis from 1990 to 2019: An analysis of the Global Burden of Disease Study 2019.

BACKGROUND: Information about global and local epidemiology and trends of skin cancers is limited, which increases the difficulty of cutaneous cancer control. METHODS: To estimate the global spatial patterns and temporal trends of skin cancer burden. Based on the GBD 2019, we collected and analyzed numbers and age-standardized rates (ASR) of skin cancer incidence, disability-adjusted life years (DALYs) and mortality (ASIR, ASDR, and ASMR) in 204 countries from 1990 through 2019 were estimated by age, sex, subtype (malignant skin melanoma [MSM], squamous-cell carcinoma [SCC], and basal-cell carcinoma [BCC]), Socio-demographic Index (SDI), region, and country. Temporal trends in ASR were also analyzed using estimated annual percentage change. RESULTS: Globally, in 2019, there were 4.0 million BCC, 2.4 million SCC, and 0.3 million MSM. There were approximately 62.8 thousand deaths and 1.7 million DALYs due to MSM, and 56.1 thousand deaths and 1.2 million DALYs were attributed to SCC, respectively. The men had higher ASR of skin cancer burden than women. The age-specific rates of global skin cancer burden were higher in the older adults, increasing trends observed from 55 years old. Geographically, the numbers and ASR of skin cancers varied greatly across countries, with the largest burden of ASIR in high SDI regions. However, an unexpected increase was observed in some regions from 1990 to 2019, such as East Asia, and Sub-Saharan Africa. Although there was a slight decrease of the ASMR and ASDR, the global ASIR of MSM dramatically increased, 1990-2019. Also, there was a remarkable increase in ASR of BCC and SCC burden. CONCLUSIONS: Skin cancer remains a major global public health threat. Reducing morbidity and mortality strategies such as primary and secondary prevention should be reconsidered, especially in the most prevalent and unexpected increased regions, especially for those areas with the greatest proportions of their population over age 55.

Space-Time Clustering Characteristics of Malaria in Bhutan at the End Stages of Elimination.

Malaria in Bhutan has fallen significantly over the last decade. As Bhutan attempts to eliminate malaria in 2022, this study aimed to characterize the space-time clustering of malaria from 2010 to 2019. Malaria data were obtained from the Bhutan Vector-Borne Disease Control Program data repository. Spatial and space-time cluster analyses of Plasmodium falciparum and Plasmodium vivax cases were conducted at the sub-district level from 2010 to 2019 using Kulldorff's space-time scan statistic. A total of 768 confirmed malaria cases, including 454 (59%) P. vivax cases, were reported in Bhutan during the study period. Significant temporal clusters of cases caused by both species were identified between April and September. The most likely spatial clusters were detected in the central part of Bhutan throughout the study period. The most likely space-time cluster was in Sarpang District and neighboring districts between January 2010 to June 2012 for cases of infection with both species. The most likely cluster for P. falciparum infection had a radius of 50.4 km and included 26 sub-districts with a relative risk (RR) of 32.7. The most likely cluster for P. vivax infection had a radius of 33.6 km with 11 sub-districts and RR of 27.7. Three secondary space-time clusters were detected in other parts of Bhutan. Spatial and space-time cluster analysis identified high-risk areas and periods for both P. vivax and P. falciparum malaria. Both malaria types showed significant spatial and spatiotemporal variations. Operational research to understand the drivers of residual transmission in hotspot sub-districts will help to overcome the final challenges of malaria elimination in Bhutan.

Spatial clustering and temporal trend analysis of international migrants diagnosed with tuberculosis in Brazil.

BACKGROUND: Tuberculosis (TB) in migrants is of concern to health authorities worldwide and is even more critical in Brazil, considering the country´s size and long land borders. The aim of the study was to identify critical areas in Brazil for migrants diagnosed with TB and to describe the temporal trend in this phenomenon in recent years. METHODS: This is an ecological study that used spatial analysis and time series analysis. As the study population, all cases of migrants diagnosed with TB from 2014 to 2019 were included, and Brazilian municipalities were considered as the unit of ecological analysis. The Getis-Ord Gi* technique was applied to identify critical areas, and based on the identified clusters, seasonal-trend decomposition based on loess (STL) and Prais-Winsten autoregression were used, respectively, to trace and classify temporal trend in the analyzed series. In addition, several municipal socioeconomic indicators were selected to verify the association between the identified clusters and social vulnerability. RESULTS: 2,471 TB cases were reported in migrants. Gi* analysis showed that areas with spatial association with TB in immigrants coincide with critical areas for TB in the general population (coast of the Southeast and North regions). Four TB clusters were identified in immigrants in the states of Amazonas, Roraima, São Paulo, and Rio de Janeiro, with an upward trend in most of these clusters. The temporal trend in TB in immigrants was classified as increasing in Brazil (+ 60.66% per year [95% CI: 27.21-91.85]) and in the clusters in the states of Amazonas, Roraima, and Rio de Janeiro (+1.01, +2.15, and + 2.90% per year, respectively). The cluster in the state of São Paulo was the only one classified as stationary. The descriptive data on the municipalities belonging to the clusters showed evidence of the association between TB incidence and conditions of social vulnerability. CONCLUSIONS: The study revealed the critical situation of TB among migrants in the country. Based on the findings, health authorities might focus on actions in regions identified, stablishing an intensive monitoring and following up, ensuring that these cases concluded their treatment and avoiding that they could spread the disease to the other regions or scenarios. The population of migrants are very dynamic, therefore strategies for following up them across Brazil are really urgent to manage the tuberculosis among international migrants in an efficient and proper way.

Spatial-temporal clustering of malaria using routinely collected health facility data on the Kenyan Coast.

BACKGROUND: The over-distributed pattern of malaria transmission has led to attempts to define malaria "hotspots" that could be targeted for purposes of malaria control in Africa. However, few studies have investigated the use of routine health facility data in the more stable, endemic areas of Africa as a low-cost strategy to identify hotspots. Here the objective was to explore the spatial and temporal dynamics of fever positive rapid diagnostic test (RDT) malaria cases routinely collected along the Kenyan Coast. METHODS: Data on fever positive RDT cases between March 2018 and February 2019 were obtained from patients presenting to six out-patients health-facilities in a rural area of Kilifi County on the Kenyan Coast. To quantify spatial clustering, homestead level geocoded addresses were used as well as aggregated homesteads level data at enumeration zone. Data were sub-divided into quarterly intervals. Kulldorff's spatial scan statistics using Bernoulli probability model was used to detect hotspots of fever positive RDTs across all ages, where cases were febrile individuals with a positive test and controls were individuals with a negative test. RESULTS: Across 12 months of surveillance, there were nine significant clusters that were identified using the spatial scan statistics among RDT positive fevers. These clusters included 52% of all fever positive RDT cases detected in 29% of the geocoded homesteads in the study area. When the resolution of the data was aggregated at enumeration zone (village) level the hotspots identified were located in the same areas. Only two of the nine hotspots were temporally stable accounting for 2.7% of the homesteads and included 10.8% of all fever positive RDT cases detected. CONCLUSION: Taking together the temporal instability of spatial hotspots and the relatively modest fraction of the malaria cases that they account for; it would seem inadvisable to re-design the sub-county control strategies around targeting hotspots.

Tendencia espacio-temporal de clasificación BIRADS sugestiva de malignidad: un análisis nacional de mastografías, 2013-2017 / Spatio-temporal trend of BIRADS classification suggestive of malignancy: a national analysis of mammograms, 2013-2017

Resumen Introducción: Promover la detección de cáncer de mama (CaMa) en mujeres mediante mastografía es una estrategia viable para disminuir los diagnósticos en fases clínicamente avanzadas y la mortalidad. Objetivos: Describir los resultados reportados por estudios de mastografía en mujeres realizados a nivel nacional durante 2013-2017 y analizar la tendencia espaciotemporal de categorías BIRADS (Breast Imaging Reporting and Data System) sugestivas de malignidad por Estado. Método: Diseño analítico longitudinal que incluyó información sobre estudios de mastografía de mujeres según grupo de edad (< 40 e ≥ 40), valoradas en unidades de la Secretaría de Salud, México, durante 2013-2017. Se estimó la frecuencia de categorías según BIRADS, tasa estandarizada sugestiva de malignidad (categorías 4 y 5) en mujeres ≥ 40 años y se utilizó estadística espacial para analizar la tendencia por Estado. Resultados: Se analizaron 3,659,151 mastografías, el 98.5 % en mujeres ≥ 40 años. La tasa sugestiva de malignidad disminuyó de 38.3 (2013) a 31 (2017) por 100 mil mujeres ≥ 40 años; sin embargo, el riesgo de detección aumentó hasta 13 veces en diez Estados. Conclusiones: Aunque el riesgo de detección en categorías sugestivas de malignidad disminuyó a nivel nacional, algunos Estados requieren reforzar la aplicación de programas de detección del CaMa mediante mastografía e incrementar la participación de la población blanco.

Abstract Introduction: Promoting breast cancer (BC) detection in women by means of mammography is a viable strategy to reduce the number of diagnoses at clinically advanced stages and mortality. Objectives: To describe the results reported by mammography studies in women, carried out nationally during 2013-2017, and to analyze the spatiotemporal trend of Breast Imaging Reporting and Data System (BIRADS) categories suggestive of malignancy by State. Method: Longitudinal, analytical design that included information on mammography studies of women according to age group (< 40 and ≥ 40), evaluated in units of the Ministry of Health of Mexico during 2013-2017. The frequency of BIRADS categories and a standardized rate suggestive of malignancy (categories 4 and 5) were estimated in women aged ≥ 40 years, and spatial statistics were used to analyze the trend by State. Results: A total of 3,659,151 mammograms were analyzed, 98.5 % in women aged ≥ 40 years. The malignancy-suggestive rate decreased from 38.3 (2013) to 31 (2017) per 100,000 women aged ≥ 40 years; however, the risk of detection increased up to 13 times in ten States. Conclusions: Although the risk of detection in categories suggestive of malignancy decreased at the national level, some States need to reinforce the application of BC detection programs through mammography and increase the participation of the target population.

Difusión espacio-temporal de muertes por COVID-19 en Argentina

[RESUMEN]. Objetivos. Describir la difusión espacio-temporal de las muertes por COVID-19, y analizar sus desigualdades socio-espaciales en la Argentina. Métodos. Se analizaron las muertes por COVID-19 ocurridas en Argentina al 17 de octubre de 2020 utilizando datos referidos al día, mes y año, y el lugar de residencia. Se utilizó la técnica de escaneo espacio-temporal por permutaciones para detectar la presencia de conglomerados espacio-temporales. Se compararon el nivel de pobreza, densidad poblacional y porcentaje de población adulta mayor entre las áreas pertenecientes a conglomerados de mortalidad alta y las áreas pertenecientes a conglomerados de mortalidad baja. Resultados. Se detectaron cinco conglomerados de mortalidad alta entre el 21 de marzo y el 27 de agosto en el Aglomerado Gran Buenos Aires (AGBA) y noreste de la provincia de Buenos Aires. Los conglomerados de mortalidad baja se localizaron en la periferia del AGBA, desde mediados de septiembre a mediados de octubre, y en el centro y noroeste de la Argentina, entre fines de abril y fines de agosto. Los conglomerados de mortalidad alta se localizaron en áreas con mayor densidad poblacional y mayor porcentaje de población adulta mayor en comparación a los conglomerados de mortalidad baja. Conclusiones. No se detectaron conglomerados de mortalidad alta entre septiembre y mediados de octubre. Tampoco hemos detectado una difusión espacial de muertes hacia áreas de nivel socioeconómico bajo a nivel nacional. Nuestros resultados apoyan el modelo de difusión de la mortalidad en una primera fase, que afecta a la principal área urbana de la Argentina.

[ABSTRACT]. Objectives. Describe the space-time spread of COVID-19 deaths and analyze its socio-spatial inequalities in Argentina. Methods. COVID-19 deaths in Argentina as of October 17, 2020 were analyzed using data on day, month, and year, and place of residence. The space-time permutation scan method was used to detect the presence of space-time clusters. Poverty levels, population densities, and percentage of older adults in the population were compared for areas in high-mortality clusters and low-mortality clusters. Results. Five high-mortality clusters were detected between March 21 and August 27 in the Greater Buenos Aires conurbation and the northeast of the province of Buenos Aires. Low-mortality clusters were located on the periphery of the urban area from mid-September to mid-October and in central and northwestern Argentina between late April and late August. High-mortality clusters were located in areas with higher population densities and higher percentages of older adults in population, compared to low-mortality clusters. Conclusions. No high-mortality clusters were detected between September and mid-October. Nor have we detected a spatial spread of deaths to areas of low socioeconomic status at the national level. Our results support the first phase of the mortality spread model, affecting the largest urban area in Argentina.

[RESUMO]. Objetivo. Descrever a distribuição espaço-temporal de mortes por COVID-19 e analisar desigualdades socioespaciais na Argentina. Métodos. As mortes por COVID-19 ocorridas na Argentina até 17 de outubro de 2020 foram analisadas a partir de dados referentes ao dia, mês e ano e local de residência. A estatística scan utilizando modelo de permutação espaço-tempo foi aplicada para detectar conglomerados espaço-temporais. Realizou-se a comparação do nível de pobreza, densidade populacional e percentual de população idosa entre as áreas pertencentes aos conglomerados com alta mortalidade e as áreas pertencentes aos conglomerados com baixa mortalidade. Resultados. Cinco conglomerados com alta mortalidade foram detectados entre 21 de março e 27 de agosto na região da Grande Buenos Aires e no nordeste da província de Buenos Aires. Os conglomerados com baixa mortalidade estavam localizados na periferia da região da Grande Buenos Aires, de meados de setembro a meados de outubro, e nas regiões central e noroeste do país, entre o final de abril e final de agosto. Os conglomerados com alta mortalidade estavam localizados em áreas de maior densidade populacional e maior percentual de população idosa em comparação aos conglomerados com baixa mortalidade. Conclusão. Não foram detectados conglomerados com alta mortalidade entre setembro e meados de outubro. Também não se observou a distribuição espacial de mortes em áreas com baixo nível socioeconômico em todo o país. Os resultados deste estudo respaldam o modelo de distribuição de mortes na primeira fase, atingindo a principal área urbana da Argentina.

Impact and trend of COVID-19 in the Brazilian prison system: an ecological study. / Impacto e tendência da COVID-19 no sistema penitenciário do Brasil: um estudo ecológico.

Given the rapid spread of new coronavirus within the prison system, this study's objective was to identify spatial clusters for the occurrence of COVID-19 in the incarcerated population and analyze temporal trends of confirmed cases in the Brazilian prison system. This ecological study considered the five Brazilian macro-regions to be units of analysis, with its 26 states and the Federal District. The population was composed of all COVID-19 cases confirmed from April 14th to August 31st, 2020. The source used to collect data was the COVID-19 Monitoring Panel from the National Prison Department. Descriptive analysis, scan statistics, and time series were performed. A total of 18,767 COVID-19 cases were reported among the incarcerated population, 4,724 in São Paulo. The scan statistic analysis resulted in 14 spatial risk clusters for COVID-19 among persons deprived of liberty; the highest-risk cluster was in the Federal District. Although the country ends the series with a decreasing behavior, a growing trend was verified in most of the study period. The conclusion is that there is a need to implement mass testing among the incarcerated population while continually monitoring and recording COVID-19 cases.

Tendo em vista a rápida disseminação do novo coronavírus no sistema prisional, o presente trabalho teve como objetivos identificar aglomerados espaciais para ocorrência da COVID-19 na população privada de liberdade (PPL) e analisar a tendência temporal dos casos confirmados no sistema penitenciário do Brasil. Estudo ecológico que considerou como unidades de análise as cinco macrorregiões do Brasil, seus 26 estados e o Distrito Federal. A população foi composta por todos os casos de COVID-19 confirmados, no período de 14 de abril a 31 de agosto de 2020. A fonte de dados utilizada foi o Painel de Monitoramento dos casos de COVID-19 nos sistemas prisionais do Departamento Penitenciário Nacional. Realizou-se análise descritiva, estatística de varredura e análise da tendência temporal. Foram notificados 18.767 casos de COVID-19 na PPL, dos quais 4.724 ocorreram no estado de São Paulo. A estatística de varredura possibilitou a identificação de 14 clusters espaciais de risco para COVID-19 na PPL, sendo o aglomerado de maior risco formado pelo Distrito Federal. Embora o país finalize a série com um comportamento decrescente, observa-se que no período de investigação a tendência apresentou um comportamento maioritariamente crescente. Evidencia-se a necessidade de testagem em massa, monitoramento e registro contínuo dos casos de COVID-19 na PPL do país.

Impacto e tendência da COVID-19 no sistema penitenciário do Brasil: um estudo ecológico / Impact and trend of COVID-19 in the Brazilian prison system: an ecological study

Resumo Tendo em vista a rápida disseminação do novo coronavírus no sistema prisional, o presente trabalho teve como objetivos identificar aglomerados espaciais para ocorrência da COVID-19 na população privada de liberdade (PPL) e analisar a tendência temporal dos casos confirmados no sistema penitenciário do Brasil. Estudo ecológico que considerou como unidades de análise as cinco macrorregiões do Brasil, seus 26 estados e o Distrito Federal. A população foi composta por todos os casos de COVID-19 confirmados, no período de 14 de abril a 31 de agosto de 2020. A fonte de dados utilizada foi o Painel de Monitoramento dos casos de COVID-19 nos sistemas prisionais do Departamento Penitenciário Nacional. Realizou-se análise descritiva, estatística de varredura e análise da tendência temporal. Foram notificados 18.767 casos de COVID-19 na PPL, dos quais 4.724 ocorreram no estado de São Paulo. A estatística de varredura possibilitou a identificação de 14 clusters espaciais de risco para COVID-19 na PPL, sendo o aglomerado de maior risco formado pelo Distrito Federal. Embora o país finalize a série com um comportamento decrescente, observa-se que no período de investigação a tendência apresentou um comportamento maioritariamente crescente. Evidencia-se a necessidade de testagem em massa, monitoramento e registro contínuo dos casos de COVID-19 na PPL do país.

Abstract Given the rapid spread of new coronavirus within the prison system, this study's objective was to identify spatial clusters for the occurrence of COVID-19 in the incarcerated population and analyze temporal trends of confirmed cases in the Brazilian prison system. This ecological study considered the five Brazilian macro-regions to be units of analysis, with its 26 states and the Federal District. The population was composed of all COVID-19 cases confirmed from April 14th to August 31st, 2020. The source used to collect data was the COVID-19 Monitoring Panel from the National Prison Department. Descriptive analysis, scan statistics, and time series were performed. A total of 18,767 COVID-19 cases were reported among the incarcerated population, 4,724 in São Paulo. The scan statistic analysis resulted in 14 spatial risk clusters for COVID-19 among persons deprived of liberty; the highest-risk cluster was in the Federal District. Although the country ends the series with a decreasing behavior, a growing trend was verified in most of the study period. The conclusion is that there is a need to implement mass testing among the incarcerated population while continually monitoring and recording COVID-19 cases.

Hierarchical networks of food exchange in the black garden ant Lasius niger.

In most eusocial insects, the division of labor results in relatively few individuals foraging for the entire colony. Thus, the survival of the colony depends on its efficiency in meeting the nutritional needs of all its members. Here, we characterize the network topology of a eusocial insect to understand the role and centrality of each caste in this network during the process of food dissemination. We constructed trophallaxis networks from 34 food-exchange experiments in black garden ants (Lasius niger). We tested the influence of brood and colony size on (i) global indices at the network level (i.e., efficiency, resilience, centralization, and modularity) and (ii) individual values (i.e., degree, strength, betweenness, and the clustering coefficient). Network resilience, the ratio between global efficiency and centralization, was stable with colony size but increased in the presence of broods, presumably in response to the nutritional needs of larvae. Individual metrics highlighted the major role of foragers in food dissemination. In addition, a hierarchical clustering analysis suggested that some domestics acted as intermediaries between foragers and other domestics. Networks appeared to be hierarchical rather than random or centralized exclusively around foragers. Finally, our results suggested that networks emerging from social insect interactions can improve group performance and thus colony fitness.