Academic literature on the topic 'Spatial epidemiological investigation'

The role of schools as a source of infection and driver in the coronavirus-pandemic has been controversial and is still not completely clarified. To prevent harm and disadvantages for children and adolescents, but also adults, detailed data on school outbreaks is needed, especially when talking about open schools employing evidence-based safety concepts. Here, we investigated the first significant COVID-19 school outbreak in Hamburg, Germany, after the re-opening of schools in 2020. Using clinical, laboratory, and contact data and spatial measures for epidemiological and environmental studies combined with whole-genome sequencing (WGS) analysis, we examined the causes and the course of the secondary school outbreak. The potential index case was identified by epidemiological tracking and the lessons in classrooms with presumably high virus spreading rates and further infection chains in the setting. Sequence analysis of samples detected one sample of a different virus lineage and 25 virus genomes with almost identical sequences, of which 21 showed 100% similarity. Most infections occurred in connection with two lesson units of the primary case. Likely, 31 students (12–14 years old), two staff members, and three family members were infected in the school or the typical household. Sequence analysis revealed an outbreak cluster with a single source that was epidemiologically identified as a member of the educational staff. In lesson units, two superspreading events of varying degrees with airborne transmission took place. These were influenced by several parameters including the exposure times, the use of respiratory masks while speaking and spatial or structural conditions at that time.

SUMMARYBetween April and August 2005 Christchurch, New Zealand experienced an outbreak of Legionnaires' disease. There were 19 laboratory-confirmed case including three deaths.Legionella pneumophilaserogroup 1 (Lpsg1) was identified as the causative agent for all cases. A case-control study indicated a geographical association between the cases but no specific common exposures. Rapid spatial epidemiological investigation confirmed the association and identified seven spatially significant case clusters. The clusters were all sourced in the same area and exhibited a clear anisotropic process (noticeable direction) revealing a plume effect consistent with aerosol dispersion from a prevailing southwesterly wind. Four out of five cases tested had indistinguishable allele profiles that also matched environmental isolates from a water cooling tower within the centre of the clusters. This tower was considered the most probable source for these clusters. The conclusion would suggest a maximum dispersal distance in this outbreak of 11·6 km. This work illustrated the value of geostatistical techniques for infectious disease epidemiology and for providing timely information during outbreak investigations.

Mosquito-borne infections are increasing in endemic areas and previously unaffected regions. In 2020, the notification rate for Dengue was 0.5 cases per 100,000 population, and for Chikungunya <0.1/100,000. In 2019, the rate for Malaria was 1.3/100,000, and for West Nile Virus, 0.1/100,000. Spatial analysis is increasingly used in surveillance and epidemiological investigation, but reviews about their use in this research topic are scarce. We identify and describe the methodological approaches used to investigate the distribution and ecological determinants of mosquito-borne infections in Europe. Relevant literature was extracted from PubMed, Scopus, and Web of Science from inception until October 2021 and analysed according to PRISMA-ScR protocol. We identified 110 studies. Most used geographical correlation analysis (n = 50), mainly applying generalised linear models, and the remaining used spatial cluster detection (n = 30) and disease mapping (n = 30), mainly conducted using frequentist approaches. The most studied infections were Dengue (n = 32), Malaria (n = 26), Chikungunya (n = 26), and West Nile Virus (n = 24), and the most studied ecological determinants were temperature (n = 39), precipitation (n = 24), water bodies (n = 14), and vegetation (n = 11). Results from this review may support public health programs for mosquito-borne disease prevention and may help guide future research, as we recommended various good practices for spatial epidemiological studies.

Echinococcus multilocularis is a tapeworm causing severe zoonotic disease in temperate Europe. Between 2018 and 2020, 68 golden jackals and 94 red foxes were investigated to determine the prevalence of E. multilocularis infection and its driving factors. The overall prevalence (golden jackal: 41.2%; red fox: 12.5%) significantly differed, whereas the mean intensities did not. The spatial scan statistics revealed three significant clusters of E. multilocularis infection. The binary logistic and ordinal regression results revealed that the golden jackal is more likely to become infected than the red fox, and the probability of infection level was also higher in jackals. Our findings highlight the golden jackal’s role, which could be as important as the red fox in the spread of this severe zoonotic agent. This micro-epidemiological approach can advance the knowledge on local drivers which facilitate the spread of E. multilocularis and could cause a relevant public health problem on the continent.

ABSTRACTMultilocus variable-number tandem-repeat analysis (MLVA) is efficient for routine typing and for investigating the genetic structures of natural microbial populations. Two distinct pathovars ofXanthomonas oryzaecan cause significant crop losses in tropical and temperate rice-growing countries. Bacterial leaf streak is caused byX. oryzaepv. oryzicola, and bacterial leaf blight is caused byX. oryzaepv. oryzae. For the latter, two genetic lineages have been described in the literature. We developed a universal MLVA typing tool both for the identification of the threeX. oryzaegenetic lineages and for epidemiological analyses. Sixteen candidate variable-number tandem-repeat (VNTR) loci were selected according to their presence and polymorphism in 10 draft or complete genome sequences of the threeX. oryzaelineages and by VNTR sequencing of a subset of loci of interest in 20 strains per lineage. The MLVA-16 scheme was then applied to 338 strains ofX. oryzaerepresenting different pathovars and geographical locations. Linkage disequilibrium between MLVA loci was calculated by index association on different scales, and the 16 loci showed linear Mantel correlation with MLSA data on 56X. oryzaestrains, suggesting that they provide a good phylogenetic signal. Furthermore, analyses of sets of strains for different lineages indicated the possibility of using the scheme for deeper epidemiological investigation on small spatial scales.

<p><strong>Abstract.</strong> This paper analyses the pattern distribution and influential risk factors of tuberculosis (TB) at 47 Sections of Shah Alam, Malaysia using spatial epidemiological (SE) approach. Quantifying environmental risk factors of the disease pattern can be a challenging task due to spatial environmental and transmission process, whereby each area may have its own unique risk factors and dynamics. A conceptual framework of spatial epidemiological data analysis (Pfieffer et al. 2008), and geographical information system (GIS) method (Chang 2011) are mainly adapted in this research method. Disease mapping of the 3-year datasets (2013 to 2015) was created using GIS analysis and satellite remote sensed land used in identifying the clustering areas of TB pattern. Meanwhile, the potential risk factors of TB in the clustering areas were assessed using spatial landscape ecology through site observation.</p><p>Figure 1 shows the spatial pattern of TB cases in the study area as a random medium, revealing that TB distribution is well distributed in the area. However, there is also some clustering concentration at the northern zone (Section U17 to Section U20) and some in U5 and U13, while in the central zone, the majority cases are concentrated at Section S7, S17, S18, S19 and S24. Section S27 and S28 are also indicated as high-case areas in the southern zone. It is interesting to note that in the recent years (2015), the disease was a little dispersed and scattered to the northern area especially in U13, U10, U15 and U17 due to the new township area, physical development and human mobility (Nava-Aguilera et al., 2011; Prussing et al., 2013). Furthermore, every zone or section may have its own risk factors; hence, there is a need for specific investigation to be conducted in a smaller area.</p>

Background Ebola Virus Disease (EVD) is a highly infectious disease that has produced over 25,000 cases in the past 50 years. While many past outbreaks resulted in relatively few cases, the 2014 outbreak in West Africa was the most deadly occurrence of EVD to date, producing over 15,000 confirmed cases. Objective In this study, we investigated population level predictors of EVD risk at the regional level in Sierra Leone, Liberia, and Guinea. Methods Spatial and descriptive analyses were conducted to assess distribution of EVD cases. Choropleth maps showing the spatial distribution of EVD risk across the study area were generated in ArcGIS. Poisson and negative binomial models were then used to investigate population and regional predictors of EVD risk. Results Results indicated that the risk of EVD was significantly lower in areas with higher proportions of: (a) the population living in urban areas, (b) households with a low quality or no toilets, and (c) married men working in blue collar jobs. However, risk of EVD was significantly higher in areas with high mean years of education. Conclusions The identified significant predictors of high risk were associated with areas with higher levels of urbanization. This may be due to higher population densities in the more urban centers and hence higher potential of infectious contact. However, there is need to better understand the role of urbanization and individual contact structure in an Ebola outbreak. We discuss shortcomings in available data and emphasize the need to consider spatial scale in future data collection and epidemiological studies.

Breast cancer (BC) mortality analysis at the regional level is important not only for assessing the current epidemiological situation, but also contributes to a better understanding of factors that may affect mortality. Aim. The purpose of the study is to assess the spatial deaths from BC in Kazakhstan. Material and methods. Investigation was retrospective between 2009-2018 years. The materials were collected by statistics Committee by the Ministry of National Economy of the Republic of Kazakhstan concerning the deaths from BC (ICD-10-C50). A method of compiling a cartogram based on the determination of the standard deviation (σ) from the mean (x) was applied. Mortality rates calculated per 100,000 female population were used. Results and discussion. A spatial assessment of breast cancer mortality was presented based on the calculation of mortality rates: low up to 12.80/0000; average from 12.8 to 17.30/0000, and high – above 17.30/0000. It was established that the North Kazakhstan (18.20/0000), Akmola (18.90/0000), East Kazakhstan (20.30/0000) and Pavlodar (22.20/0000) regions, as well as the city of Almaty (21.70/0000) relate to regions with high mortality rates. Conclusion. Features of mortality from BC in the republic have been established, while a spatial assessment (cartogram) of mortality indicates regions with different mortality rates. The obtained data are recommended to be used for monitoring and evaluation of anti-cancer measures – BC screening. Keywords: mortality, breast cancer, cartogram, Kazakhstan.

Abstract Background Population movement could extend multidrug-resistant tuberculosis (MDR-TB) transmission and complicate its global prevalence. We sought to identify the high-risk populations and geographic sites of MDR-TB transmission in Shenzhen, the most common destination for internal migrants in China. Methods We performed a population-based, retrospective study in patients diagnosed with MDR-TB in Shenzhen during 2013–2017. By defining genomic clusters with a threshold of 12–single-nucleotide polymorphism distance based on whole-genome sequencing of their clinical strains, the clustering rate was calculated to evaluate the level of recent transmission. Risk factors were identified by multivariable logistic regression. To further delineate the epidemiological links, we invited the genomic-clustered patients to an in-depth social network investigation. Results In total, 105 (25.2%) of the 417 enrolled patients with MDR-TB were grouped into 40 genome clusters, suggesting recent transmission of MDR strains. The adjusted risk for student to have a clustered strain was 4.05 (95% confidence interval, 1.06–17.0) times greater than other patients. The majority (70%, 28/40) of the genomic clusters involved patients who lived in different districts, with residences separated by an average of 8.76 kilometers. Other than household members, confirmed epidemiological links were also identified among classmates and workplace colleagues. Conclusions These findings demonstrate that local transmission of MDR-TB is a serious problem in Shenzhen. While most transmission occurred between people who lived distant from each other, there was clear evidence that transmission occurred in schools and workplaces, which should be included as targeted sites for active case finding. The average residential distance between genomic-clustered cases was more than 8 kilometers, while schools and workplaces, identified as sites of transmission in this study, deserve increased vigilance for targeted case finding of multidrug-resistant tuberculosis.

ObjectivesGlobal prevalence rates of psoriasis differ significantly, with lowest rates in the equator region and increasing tendencies towards the north but also differences within-country. Information on regional variations in Germany is missing. This study aims to analyse the change of psoriasis prevalence in Germany over time and to detect regional variations.DesignCross sectional, spatio-epidemiological study on regional psoriasis prevalence in Germany.SettingClaims data study based on nationwide outpatient billing data on county level.MethodsAnalyses based on outpatient billing data for 2010–2017 derived from all people insured in statutory health insurances (about 72.8 million). We performed descriptive spatio-temporal analyses of prevalence rates using probability mapping and statistical smoothing methods, identified spatial clusters and examined a north-south gradient using spatial statistics.ResultsThe prevalence increased from 147.4 per 10 000 in 2010 to 173.5 in 2017. In 2017, counties’ prevalence rates ranged between 93.8 and 340.9. Decreased rates occurred mainly in southern counties, increased rates in northern and eastern counties. Clusters of low rates occur in southern and south-western Germany, clusters of high rates in the north and north-east. The correlation between counties’ latitudes and their prevalence rates was high with Pearson’s r=0.65 (p<0.05).ConclusionIncreased prevalence of psoriasis over time and marked regional variations in Germany were observed which need further investigation.

Sport and leisure injuries are recognised as a public health issue in Australia. Despite the many health benefits associated with sport and leisure participation, there is a risk of sustaining injury during participation. To keep Australia active, there is a critical need to prevent injury occurrence. Epidemiological investigations in sport and leisure injuries have been largely examined by grouping of sports, age groups, sex and level of play. In addition, intrinsic (person-level) factors have been considered, such as strength, flexibility or previous injury history. These factors may not be sufficient to identify injury burden or prevent an increase in injury incidences. In the broader injury literature (e.g., road traffic crashes or drowning), it is known that injuries often cluster within specific places (i.e., road intersections or bodies of water). These specific geographic locations may also relate to sport and leisure injuries (e.g., sports grounds or facilities). Similarly, population-level factors such as socio-economic status or cultural groups within an area could influence the types of sports and leisure activities people participate in and consequently, the injuries that occur. A review presented in this PhD thesis revealed that there is very limited sport and leisure injury epidemiological information from a geographical perspective. To address this gap, and determine whether there is a spatial pattern in sport/leisure injuries, the aim of this PhD was to examine the geospatial distribution of sport/leisure injury hospitalisations and their association with a broad range of social and economic characteristics. This thesis uses spatial epidemiological methods to answer questions such as ‘Where do sports and leisure injuries occur?’ and ‘In whom do sports/leisure injuries occur?’ The main chapters present the results of the application of spatial epidemiological methods to describe the problem, to test hypotheses and to explore associations with possible explanatory variables. The findings showed a significant variation across metropolitan, regional and rural areas in the pattern and clustering of injuries when examining different sports, age groups and other variables such as education level. A secondary aim of this thesis was to consider the dissemination of sport and injury epidemiological data. As emphasised in the literature, there is limited spatial epidemiological information available to decision-makers and key stakeholders. At best, descriptive maps might be included in a report or research paper. However, these are static and limited to the results that the author chooses to present. Therefore, an important output from this PhD is a web-GIS application that has been specifically built to enable the exploratory analysis of sport/leisure injuries in Victoria. Sport and leisure injury prevention strategies and policy development relies on information about where, when, to whom and how sport/leisure injuries occur. This thesis demonstrates that a spatial epidemiological approach is an important and novel way to address epidemiological questions from a geographical perspective.
Doctor of Philosophy

Background: Human echinococcoses are zoonotic parasitic diseases of major public health importance globally. According to recent estimates, the geographical distribution of echinococcosis is expanding and becoming an emerging and re-emerging problem in several regions of the world. Echinococcosis endemicity is geographically heterogeneous and might be affected by global environmental change over time. The aims of my research were: 1) to assess and quantify the spatiotemporal variation in land cover and climate change in Ningxia Hui Autonomous Region (NHAR); 2) to identify highly endemic areas for human echinococcoses in NHAR, and to determine the environmental covariates that have shaped the local geographical distribution of the disease; 3) to develop spatial statistical models that explain and predict the spatiotemporal variation of human exposure to Echinococcus spp. in a highly endemic county of NHAR; and 4) to analyse associations between the environment and the spatiotemporal variation of human exposure to the parasites and dog infections with Echinococcus granulosus and Echinococcus multilocularis in four echinococcosis-endemic counties of NHAR. Methods: Data on echinococcosis infections and human exposure to E. granulosus and E. multilocularis were obtained from different sources: 1) A hospital-based retrospective survey of human echinococcosis cases in NHAR between 1992 and 2013; 2) three cross-sectional surveys of school children conducted in Xiji County in 2002–2003, 2006–2007 and 2012–2013; and 3) A cross-sectional survey of human exposure and dog infections with E. granulosus and E. multilocularis conducted in Xiji, Haiyuan, Guyuan and Tongxin Counties. Environmental data were derived from high-resolution (30 m) imagery from Landsat 4/5-TM and 8-OLI and meteorological reports provided by the Chinese Academy of Sciences. Image analysis techniques and a Bayesian statistical framework were used to conduct a land cover change detection analyses and to develop regression models that described and quantified climate trends and the environmental factors associated with echinococcosis risk at different spatial scales. Results: The land cover changes observed in NHAR from 1991 to 2015 concurred with the main goals of a national policy on payments for ecosystem services, implemented in the Autonomous Region, in increasing forest and herbaceous vegetation coverages and in regenerating bareland. Statistically significant positive trends were observed in annual, summer and winter temperatures in most of the region, and a small magnitude change was found in annual precipitation, in the same 25-year period. The south of NHAR was identified as a highly endemic area for cystic echinococcosis (CE; caused by E. granulosus) and alveolar echinococcosis (AE; caused by E. multilocularis). Selected environmental covariates explained most of the spatial variation in AE risk, while the risk of CE appeared to be less spatially variable at the township level. The risk of exposure to E. granulosus expanded across Xiji County from 2002–2013, while the risk of exposure to E. multilocularis became more confined in communities located in the south of this highly endemic area. In 2012–2013, the predicted seroprevalences of human exposure to E. granulosus and dog infection with this parasite were characterised by similar geographical patterns across Xiji, Haiyuan, Guyuan and Tongxin Counties. By contrast, the predicted high seroprevalence areas for human exposure and dog infection with E. multilocularis did not coincide spatially. Climate, land cover and landscape fragmentation played a key role in explaining some of the observed spatial variation in the risk of infection with Echinococcus spp. among schoolchildren and dogs in the south of NHAR at the village level. Conclusions: The findings of this research defined populations at a high risk of human exposure to E. granulosus and E. multilocularis in NHAR. The research provides evidence on the potential effects of landscape regeneration projects on the incidence of human echinococcoses due to the associations found between the infections and regenerated land. This information will be essential to track future requirements for scaling up and targeting the control strategies proposed by the National Action Plan for Echinococcosis Control in China and may facilitate the design of future ecosystem management and protection policies and a more effective response to emerging local environmental risks. The predictive models developed as part of this research can also be used to monitor echinococcosis infections and the emergence in Echinococcus spp. transmission in the most affected areas.

Geographic information systems or geographic information science is a combination of computer-mapping capabilities with additional database management/data analysis tools. GIS is widely used in various sectors such as environmental science, urban planning, agricultural applications etc. Public health is another focus area, where GIS has been used for research and practice areas such as epidemic surveillance and monitoring, among others. The journey of use of GIS in public health spans more than a century and GIS application in public health has evolved from the simple maps to the higher level geostatistical analysis and interactive WebGIS in recent times. GIS is an analytical tool which differs from conventional computer-assisted mapping and any statistical analysis programs in its ability to analyze complex data and visual presentation of spatial data. Specialized GIS techniques such as network analysis, location-allocation models, site selection, transportation models, and geostatistical analysis are well established and used in many developed and developing nations. Unfortunately owing to the high cost of licensed software and specialized skills for advanced data analysis, use of these techniques is limited mainly for the research and by few experts. GIS is proved to be useful for various public health practices and research purposes including epidemiological surveys/investigation, implementation research, program/policy decision making and dissemination of information. The advantage of using GIS is that maps provide an added dimension to data analysis, which helps in visualizing the complex patterns and relationships of public health issues, thus many unanswered questions in public health, can be understood well through use of GIS techniques. Use of GIS in public health is an application area still in its infancy. Wider use of GIS for public health practice such as program planning, implementation and monitoring in addition to building evidence base for the policy making will help reduce inequities in health and provide universal healthcare. Overall, GIS is a helpful and efficient tool especially for public health professionals working in low resource settings. In the future with inclusion of advanced GIS technology like WebGIS can help reach the goal of optimal health care services globally.

Geographic information systems or geographic information science is a combination of computer-mapping capabilities with additional database management/data analysis tools. GIS is widely used in various sectors such as environmental science, urban planning, agricultural applications etc. Public health is another focus area, where GIS has been used for research and practice areas such as epidemic surveillance and monitoring, among others. The journey of use of GIS in public health spans more than a century and GIS application in public health has evolved from the simple maps to the higher level geostatistical analysis and interactive WebGIS in recent times. GIS is an analytical tool which differs from conventional computer-assisted mapping and any statistical analysis programs in its ability to analyze complex data and visual presentation of spatial data. Specialized GIS techniques such as network analysis, location-allocation models, site selection, transportation models, and geostatistical analysis are well established and used in many developed and developing nations. Unfortunately owing to the high cost of licensed software and specialized skills for advanced data analysis, use of these techniques is limited mainly for the research and by few experts. GIS is proved to be useful for various public health practices and research purposes including epidemiological surveys/investigation, implementation research, program/policy decision making and dissemination of information. The advantage of using GIS is that maps provide an added dimension to data analysis, which helps in visualizing the complex patterns and relationships of public health issues, thus many unanswered questions in public health, can be understood well through use of GIS techniques. Use of GIS in public health is an application area still in its infancy. Wider use of GIS for public health practice such as program planning, implementation and monitoring in addition to building evidence base for the policy making will help reduce inequities in health and provide universal healthcare. Overall, GIS is a helpful and efficient tool especially for public health professionals working in low resource settings. In the future with inclusion of advanced GIS technology like WebGIS can help reach the goal of optimal health care services globally.