Spatial distribution of tuberculosis and its socioeconomic influencing factors in mainland China 2013–2016

Wang, Qi; Guo, Liang; Wang, Jing; Zhang, Leijie; Zhu, Wanqi; Yuan, Ying; Li, Juansheng

doi:10.1111/tmi.13289

Cited by 26 publications

(33 citation statements)

References 23 publications

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“…In the present study, we also found that the number of doctors was strongly related to the COVID-19 risk in typical labor export provinces. Similar to our work, studies by Wang and Du showed that the abundance of medical resources and level of medical accessibility in a region play a vital role in the prevention of infectious diseases [ 33 , 34 ]. Therefore, improving the abundance of medical resources and level of medical accessibility in a region is an effective measure to prevent and control the local spread of infectious diseases.…”

Section: Discussionsupporting

confidence: 86%

Spatiotemporal heterogeneity and its determinants of COVID-19 transmission in typical labor export provinces of China

Wang

et al. 2021

BMC Infect Dis

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Background Previous studies have indicated that the risk of infectious disease spread is greatest in locations where a population has massive and convenient access to the epicenter of an outbreak. However, the spatiotemporal variations and risk determinants of COVID-19 in typical labor export regions of China remain unclear. Understanding the geographical distribution of the disease and the socio-economic factors affecting its transmission is critical for disease prevention and control. Methods A total of 2152 COVID-19 cases were reported from January 21 to February 24, 2020 across the 34 cities in Henan and Anhui. A Bayesian spatiotemporal hierarchy model was used to detect the spatiotemporal variations of the risk posed by COVID-19, and the GeoDetector q statistic was used to evaluate the determinant power of the potential influence factors. Results The risk posed by COVID-19 showed geographical spatiotemporal heterogeneity. Temporally, there was an outbreak period and control period. Spatially, there were high-risk regions and low-risk regions. The high-risk regions were mainly in the southwest areas adjacent to Hubei and cities that served as economic and traffic hubs, while the low-risk regions were mainly in western Henan and eastern Anhui, far away from the epicenter. The accessibility, local economic conditions, and medical infrastructure of Wuhan in Hubei province all played an important role in the spatiotemporal heterogeneity of COVID-19 transmission. The results indicated that the q statistics of the per capita GDP and the proportion of primary industry GDP were 0.47 and 0.47, respectively. The q statistic of the population flow from Wuhan was 0.33. In particular, the results showed that the q statistics for the interaction effects between population density and urbanization, population flow from Wuhan, per capita GDP, and the number of doctors were all greater than 0.8. Conclusions COVID-19 showed significant spatiotemporal heterogeneity in the labor export regions of China. The high-risk regions were mainly located in areas adjacent to the epicenter as well as in big cities that served as traffic hubs. Population access to the epicenter, as well as local economic and medical conditions, played an important role in the interactive effects of the disease transmission.

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Section: Discussionsupporting

confidence: 86%

Spatiotemporal heterogeneity and its determinants of COVID-19 transmission in typical labor export provinces of China

Wang

et al. 2021

BMC Infect Dis

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“…Studies from China and Ethiopia also reported that low access to health care services was associated with increased number of TB cases. [26,33].…”

Section: Plos Onementioning

confidence: 99%

Spatial distribution of Mycobacterium Tuberculosis in metropolitan Harare, Zimbabwe

et al. 2020

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Introduction The contribution of high tuberculosis (TB) transmission pockets in propagating area-wide transmission has not been adequately described in Zimbabwe. This study aimed to describe the presence of hotspot transmission of TB cases in Harare city from 2011 to 2012 using geospatial techniques. Methods Anonymised TB patient data stored in an electronic database at Harare City Health department was analysed using geospatial methods. Confirmed TB cases were mapped using geographic information system (GIS). Global Moran's I and Anselin Local Moran's I (LISA) were used to assess clustering and the local Getis-Ord G i * was used to estimate hotspot phenomenon of TB cases in Harare City for the period between 2011 and 2012. Results A total of 12,702 TB cases were accessed and mapped on the Harare City map. In both 2011 and 2012, ninety (90%) of cases were new and had a high human immunodeficiency virus (HIV)/TB co-infection rate of 72% across all suburbs. Tuberculosis prevalence was highest in the Southern district in both 2011 and 2012. There were pockets of spatial distribution of TB prevalence across West South West, Southern, Western, South Western and Eastern health districts. TB hot spot occurrence was restricted to the West South West, parts of South Western, Western health districts. West South West district had an increased peri-urban population with inadequate social services including health facilities. These

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“…Per capita GDP can provide insights into the effect of in macro-level economic determinants and the effects of policy on spatio-temporal variations in elderly TB incidence. Previous studies indicated that per capita GDP was significantly associated with TB incidence at the country or provincial level [ 12 , 33 – 35 ]. A country with a high level of per capita GDP can allocate greater financial resources to TB control.…”

Section: Discussionmentioning

confidence: 99%

“…Based on current evidence, income, education, occupation and population density account for most health inequalities within countries [ 11 – 15 ]. Furthermore, unbalanced regional development, with resulting consequences for socio-economic conditions, plays an important role in the incidence of TB [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development

Wang

et al. 2021

BMC Public Health

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Background Previous research pointed to a close relationship between the incidence of tuberculosis (TB) in aging populations and socio-economic conditions, however there has been lack of studies focused on a region of unbalanced socio-economic development. The aim of this paper is to explore the spatio-temporal variation in TB incidence and examine risk determinants of the disease among aging populations in a typical region. Methods Data on TB-registered cases between 2009 and 2014, in addition to social-economic factors, were collected for each district/county in Beijing, Tianjin and Hebei, a region characterized by an aging population and disparities in social-economic development. A Bayesian space–time hierarchy model (BSTHM) was used to reveal spatio-temporal variation in the incidence of TB among the elderly in this region between 2009 to 2014. GeoDetector was applied to measure the determinant power (q statistic) of risk factors for TB among the elderly. Results The incidence of TB among the elderly exhibited geographical spatial heterogeneity, with a higher incidence in underdeveloped rural areas compared with that in urban areas. Hotspots of TB incidence risk among the elderly were mostly located in north-eastern and southern areas in the study region, far from metropolitan areas. Areas with low risk were distributed mainly in the Beijing-Tianjin metropolitan areas. Social-economic factors had a non-linear influence on elderly TB incidence, with the dominant factors among rural populations being income (q = 0.20) and medical conditions (q = 0.17). These factors had a non-linear interactive effect on the incidence of TB among the elderly, with medical conditions and the level of economic development having the strongest effect (q = 0.54). Conclusions The findings explain spatio-temporal variation in TB incidence and risk determinants of elderly TB in the presence of disparities in social-economic development. High-risk zones were located mainly in rural areas, far from metropolitan centres. Medical conditions and the economic development level were significantly associated with elderly TB incidence, and these factors had a non-linear interactive effect on elderly TB incidence. The findings can help to optimize the allocation of health resources and to control TB transmission in the aging population in this region.

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Spatial distribution of tuberculosis and its socioeconomic influencing factors in mainland China 2013–2016

Cited by 26 publications

References 23 publications

Spatiotemporal heterogeneity and its determinants of COVID-19 transmission in typical labor export provinces of China

Spatiotemporal heterogeneity and its determinants of COVID-19 transmission in typical labor export provinces of China

Spatial distribution of Mycobacterium Tuberculosis in metropolitan Harare, Zimbabwe

Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development

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