Geospatial Health最新文献

Rabies continues to be one of the deadliest, high risk diseases worldwide, posing a severe threat to public health. The lack of human-to-human transmission means that the spread of rabies is not significantly affected by the distribution of humans or migra- tion. Thus, the spatiotemporal dynamic of cases in both wild and domestic animals is an important issue that can result in human cases. This paper gives an overview of the methodologies for the spatial and temporal dynamic analysis of this disease. It introduces the most representative research progress of spatial aggregation, dynamic transmission, spatiotemporal distribution, epidemiologi- cal analysis and application of modelling in the study of rabies transmission in recent years. This overview should be useful for investigating the spatial and temporal dynamics of rabies, as it could help understanding the spread of cases as well as contribute to the development of better prevention and control strategies in ecology and epidemiology.

The burden of diabetes mellitus (DM), one of the major noncommunicable diseases (NCDs), has been significantly rising globally. In the Asia-Pacific region, Thailand ranks within the top ten of diabetic patient populations and the disease has increased from 2.3% in 1991 to 8.0% in 2015. This study applied local indicators of spatial association (LISA) and spatial regression to examine the local associations in Thailand with night-time light, spatial density of alcohol/convenience stores, concentration of elderly population and prevalence of DM among middle-aged and elderly people. Univariate LISA identified the statistically significant cluster of DM prevalence in the upper north-eastern region. For multivariate spatial analysis, the obtained R2 values of the spatial lag model (SLM) and spatial error model (SEM) were 0.310 and 0.316, respectively. These two models indicated a statistical significant association of several sociodemographic and environmental characteristics with the DM prevalence: food shops (SLM coefficient = 9.625, p<0.001; SEM coefficient = 9.695, p<0.001), alcohol stores (SLM coefficient = 1.936, p<0.05; SEM coefficient = 1.894, p<0.05), population density of elderly people (SLM coefficient = 0.156, p<0.05; SEM coefficient = 0.188, p<0.05) and night-time light density (SLM coefficient = -0.437, p<0.001; SEM coefficient = -0.437, p<0.001). These findings are useful for policymakers and public health professionals in formulating measures aimed at reducing DM burden in the country.

Leptospirosis is a serious public health problem in Brazil, which can be observed after flooding events. Using an exploratory mixed clustering method, this ecological study analyzes whether spatial-temporal clustering patterns of leptospirosis occur in Brazil. Data from the Brazilian Unified Health System (SUS) were used to calculate the prevalence of leptospirosis between 2007 and 2017 in all counties of the country. Clustering techniques, including spatial association indicators, were used for analysis and evaluation of disease yearly spatial distribution. Based on Local Indicators of Spatial Association (LISA) with Empirical Bayesian rates detected spatial patterns of leptospirosis ranging from 0.137 (p = 0.001 in 2009) to 0.293 (p = 0.001 in 2008). Over the whole period, the rate was 0.388 (p = 0.001). The main pattern showed permanence of leptospirosis clusters in the South and emergence and permanence of such clusters in northern Brazil. The municipalities with leptospirosis cases and at least one flood occurrence registered in the Brazilian Integrated Disaster Information System were incorporated into the LISA cluster map with Empirical Bayesian rates. These counties were expected to exhibit clustering, not all did. The results of the cluster analysis suggest allocation of health resources in areas with leptospirosis clustering.

We provide a novel approach to understanding the multiple causations of maternal anaemia in a geospatial context, highlighting how genetics, environment and socioeconomic disparities at the micro-geographical level lead to the inequitable distribution of anaemia. All first-trimester pregnant women registered for the antenatal care programme in Anuradhapura District, Sri Lanka from July to September 2019 were invited to the Rajarata Pregnancy Cohort (RaPCo), which assessed the prevalence of anaemia in early pregnancy. The combination of the prevalence of anaemia and minor haemoglobinopathy-related anaemia (MHA) with the poverty headcount index of the 22 health divisions in the district was investigated using GeoDa spatial K-means clustering. Sociodemographic and economic data at the divisional level were compared between identified clusters. Combining the analysis with the geographical and environmental characteristics of the region, further hypotheses regarding anaemia in this community were formulated. The study included data from 3,137 pregnant women in early pregnancy. The anaemia and MHA prevalence varied from 13.6 to 21.7% and from 2.6% to 5%, respectively. We identified four distinct spatial clusters. The cluster with the highest anaemia prevalence also included high poverty and the highest prevalence of MHA. The clusters had significant differences with regard to ethnic distribution, access to water, sanitation and dietary patterns. Areas supplied by major irrigation projects had significantly low levels of anaemia, probably attributable to internal migration and improved livelihood. It was evident that genetic, socioeconomic and environmental risk factors were grouped at the divisional level, and that their complex interactions make controlling anaemia with blanket interventions unsuccessful. Analysis of the distribution of heterogeneous risk factors at the micro-geospatial level helped identify context-specific approaches to tackle anaemia in pregnancy.

We intend to tackle two under-addressed issues in access to healthcare services during the COVID-19 pandemic: first, the spatiotemporal dynamic of access during the pandemic of acute communicable disease; second, the demographic and socioeconomic access disparities. We used the two-step floating catchment area (2SFCA) method to measure the spatial access to public hospitals during the second COVID-19 wave (September 28th-February 28th, 2021) in Nottinghamshire, UK. To investigate the temporal variation in access along with the development of the pandemic, we divided our study period into 11 sections and applied the 2SFCA to each of them. The results indicate that western Nottinghamshire is better than the eastern part from a spatial perspective and the north-western urban area represents the highest spatial access; temporally, the accessibility of the public hospitals generally decreased when the number of cases increased. Particular low accessibility was observed at the beginning of the pandemic when the outbreak hit the university region and its vicinities during the back-to-school season. Our disparity analysis found that i) the access of the senior population to public hospitals deviated from that of the general population, ii) the access was positively associated with socioeconomic status, and iii) all disparities were related to the urban-rural discrepancy. These findings can help to plan temporary clinics or hospitals during epidemic emergencies. More generally, they provide scientific support to pandemic-related healthcare resource allocation and policy- making, particularly for people in vulnerable areas.

The mother-to-child transmission (MTCT) of the human immunodeficiency virus (HIV) remains a serious public health problem in the Brazilian Rainforest. This study aimed to spatially analyze this type of infection between 2007 and 2018 in Pará, which is the second-largest Brazilian state in the Brazilian Rainforest and also has the highest MTCT of HIV in Brazil. We analyzed the incidence rates of HIV (including the acquired immunodeficiency syndrome (AIDS) by MTCT as the main route of infection in children younger than 13 years old and whose mothers live in Pará. We employed spatial autocorrelation, spatial scanning, and geographic-weighted spatial regression techniques. In the period of this study, 389 new HIV/AIDS were noted, with territorial expansion of the incidence rates in the municipalities in northern and southern Pará having the highest rates. São Francisco do Pará had high spatial risk and high-spatiotemporal risk clusters comprising municipalities in western and south-western Pará between 2013 and 2016. The spatial variability of HIV/AIDS incidence rates was found to be common in the number of men and women with formal jobs; unemployed ≥18 years old people; elementary school pupils; and families enrolled in the "Single Registry for Social Programs". The social equity approach in Pará guarantee pregnant women access to preventive, diagnostic and treatment health services and their children should be supported to eliminate the MTCT of HIV in Pará.

Afghanistan continues to experience challenges affecting polio eradication. Mass polio vaccination campaigns, which aim to protect children under the age of 5, are a key eradication strategy. To date, the polio program in Afghanistan has only employed facility-based seroprevalence surveys, which can be subject to sampling bias. We describe the feasibility in implementing a cross-sectional household poliovirus seroprevalence survey based on geographical information systems (GIS) in three districts. Digital maps with randomly selected predetermined starting points were provided to teams, with a total target of 1,632 households. Teams were instructed to navigate to predetermined starting points and enrol the closest household within 60 m. To assess effectiveness of these methods, we calculated percentages for total households enrolled with valid geocoordinates collected within the designated boundary, and whether the Euclidean distance of households were within 60 m of a predetermined starting point. A normalized difference vegetation index (NDVI) image ratio was conducted to further investigate variability in team performances. The study enrolled a total of 78% of the target sample with 52% of all households within 60 m of a pre-selected point and 79% within the designated cluster boundary. Success varied considerably between the four target areas ranging from 42% enrolment of the target sample in one place to 90% enrolment of the target sample in another. Interviews with the field teams revealed that differences in security status and amount of non-residential land cover were key barriers to higher enrolment rates. Our findings indicate household poliovirus seroprevalence surveys using GIS-based sampling can be effectively implemented in polio endemic countries to capture representative samples. We also proposed ways to achieve higher success rates if these methods are to be used in the future, particularly in areas with concerns of insecurity or spatially dispersed residential units.

Worldwide, policies to combat human immunodeficiency virus (HIV) have led to a small decrease in the acquired immunodeficiency syndrome (AIDS) mortality rate among young people. For greater policy efficacy, it is necessary to determine the influence of social determinants of health (SDHs) in each territory. The objective of this study was to spatially analyse the AIDS mortality rate among young people in a province of the Brazilian Amazon and the spatial variability of the rate promoted by SDHs. All reports of AIDS deaths between 2007 and 2018 among young people living in the state of Pará were included in the study. The mortality rate was analysed using spatial distribution and autocorrelation, spatial scanning, and geographically weighted regression (GWR). During the study period, there were 1,372 deaths from AIDS among young people with a territorial expansion. The spatial autocorrelation showed two high-high clusters in the period from 2007 to 2010, one formed by municipalities in south-eastern Pará and one in the metropolitan region of Belém, with only the latter remaining between 2011 and 2018. This region showed a higher spatial risk for AIDS mortality and was the only cluster with spatiotemporal risk in the 2013-2018 period. Spatial variability was promoted by the i) the youth homicide rate, ii) the elementary school dropout rate and iii) the number of families registered in the Unified Registry for Social Programs (CadÚnico). This study provides support for the implementation of effective focal policies to combat HIV and reduce the mortality rate among young people in Pará.

Providing equal geographical access to hospitals, either in the public or private healthcare sector, is vital and will benefit public health in general. Against the background of the partial privatization of the healthcare sector, the impact of private hospitals on equal healthcare access has been a highly neglected issue. We have applied an assessment methodology to study this situation by comparing the status quo scenario with one without private hospitals, based on accessibility analysis and spatial equality measurements. The case study of Beijing, China revealed a double-sided impact. With the presence of private hospitals, the Gini coefficient of spatial accessibility in urban districts was reduced from 0.03391 to 0.03211, while it increased from 0.1734 to 0.1914 in suburban districts. Thus, private hospitals improved spatial equality in urban districts in Beijing but jeopardized it in suburban districts. These research findings should enlighten policymakers to promote healthcare equality but would also need to be repeated in some other big cities.

After the fifth wave of the COVID-19 outbreak in May 2022, the Hong Kong government decided to ease the restrictions policy step by step. The main change was to re-open some venues that people like to visit and extend the hours of operation. With the implementation of the relaxed policy, however, the number of confirmed cases rose again. As a result, further relaxation was delayed. As an evaluation of the effectiveness of the restrictions policy could be a reference for future policies balancing viral spread and functionality of society, this paper aimed to respond to this question from the spatial point distribution view. The time, from late March 2020 to February 2021, during which the related policies took place was divided into six periods based on the policy trend (tightening or relaxing). The two-variable Ripley's Kfunction was applied for each period to explore the spatial dependence between confirmed cases and venues as changes in the spatial pattern can reveal the effect of the policy. The results show that, as time passed, the clustering degree decreased and reached its lowest level from August to mid-November 2020, then significantly increased, with the extent of clustering becoming more remarkable and the significant cluster size widening. Our results indicate that the policy had a positive effect on suppressing the spread of the virus in mid-July 2020. Then, with the virus infiltrating the community, the policy had little impact on containing the virus but likely contributed to avoid further infection.