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

Spatial pattern of isoniazid-resistant tuberculosis and its associated factors among a population with migrants in China: a retrospective population-based study

Background

Isoniazid-resistant, rifampicin-susceptible tuberculosis (Hr-TB) globally exhibits a high prevalence and serves as a potential precursor to multidrug-resistant tuberculosis (MDR-TB). Recognizing the spatial distribution of Hr-TB and identifying associated factors can provide strategic entry points for interventions aimed at early detection of Hr-TB and prevention of its progression to MDR-TB. This study aims to analyze spatial patterns and identify socioeconomic, demographic, and healthcare factors associated with Hr-TB in Shanghai at the county level.

Method

We conducted a retrospective study utilizing data from TB patients with available Drug Susceptible Test (DST) results in Shanghai from 2010 to 2016. Spatial autocorrelation was explored using Global Moran's I and Getis-Ord G i ∗ statistics. A Bayesian hierarchical model with spatial effects was developed using the INLA package in R software to identify potential factors associated with Hr-TB at the county level.

Results

A total of 8,865 TB patients with DST were included in this analysis. Among 758 Hr-TB patients, 622 (82.06%) were new cases without any previous treatment history. The drug-resistant rate of Hr-TB among new TB cases in Shanghai stood at 7.20% (622/8014), while for previously treated cases, the rate was 15.98% (136/851). Hotspot areas of Hr-TB were predominantly situated in southwestern Shanghai. Factors positively associated with Hr-TB included the percentage of older adult individuals (RR = 3.93, 95% Crl:1.93-8.03), the percentage of internal migrants (RR = 1.35, 95% Crl:1.15-1.35), and the number of healthcare institutions per 100 population (RR = 1.17, 95% Crl:1.02-1.34).

Conclusion

We observed a spatial heterogeneity of Hr-TB in Shanghai, with hotspots in the Songjiang and Minhang districts. Based on the results of the models, the internal migrant population and older adult individuals in Shanghai may be contributing factors to the emergence of areas with high Hr-TB notification rates. Given these insights, we advocate for targeted interventions, especially in identified high-risk hotspots and high-risk areas.

Toward tuberculosis elimination by understanding epidemiologic characteristics and risk factors in Hainan Province, China

BACKGROUND

The disease burden of tuberculosis (TB) was heavy in Hainan Province, China, and the information on transmission patterns was limited with few studies. This atudy aims to further explore the epidemiological characteristics and influencing factors of TB in Hainan Province, and thereby contribute valuable scientific evidences for TB elimination in Hainan Province.

METHODS

The TB notification data in Hainan Province from 2013 to 2022 were collected from the Chinese National Disease Control Information System Tuberculosis Surveillance System, along with socio-economic data. The spatial-temporal and population distributions were analyzed, and spatial autocorrelation analysis was conducted to explore TB notification rate clustering. In addition, the epidemiological characteristics of the cases among in-country migrants were described, and the delay pattern in seeking medical care was investigated. Finally, a geographically and temporally weighted regression (GTWR) model was adopted to analyze the relationship between TB notification rate and socio-economic indicators. The tailored control suggestions in different regions for TB elimination was provided by understanding epidemiological characteristics and risk factors obtained by GTWR.

RESULTS

From 2013 to 2022, 64,042 cases of TB were notified in Hainan Province. The estimated annual percentage change of TB notification rate in Hainan Province from 2013 to 2020 was - 6.88% [95% confidence interval (CI): - 5.30%, - 3.69%], with higher rates in central and southern regions. The majority of patients were males (76.33%) and farmers (67.80%). Cases among in-country migrants primarily originated from Sichuan (369 cases), Heilongjiang (267 cases), Hunan (236 cases), Guangdong (174 cases), and Guangxi (139 cases), accounting for 53%. The majority (98.83%) of TB cases were notified through passive case finding approaches, with delay in seeking care. The GTWR analysis showed that gross domestic product per capita, the number of medical institutions and health personnel per 10,000 people were main factors affecting the high TB notification rates in some regions in Hainan Province. Different regional tailored measures such as more TB specialized hospitals were proposed based on the characteristics of each region.

CONCLUSIONS

The notification rate of TB in Hainan Province has been declining overall but still remained high in central and southern regions. Particular attention should be paid to the prevalence of TB among males, farmers, and out-of-province migrant populations. The notification rate was also influenced by economic development and medical conditions, indicating the need of more TB specialized hospitals, active surveillance and other tailored prevention and control measures to promote the progress of TB elimination in Hainan Province.

The environmental and socioeconomic effects of tuberculosis patients in the southwest of China: a population-based study

OBJECTIVE

The objective of this study was to assess the incidence of tuberculosis (TB) and find the risk factors of TB patients with a high burden of TB in socioeconomic level, the high level of TB incidence and the great changes of economic and social factors, explore the possible factors, construct scientific and robust prediction model, and analyse whether the task of stopping TB can be accomplished by the expected global deadline.

STUDY DESIGN

This was an ecological study.

METHODS

Descriptive analysis, spatial and space-time scan, correlation analysis, and regression analysis were carried out, based on cases of TB in Sichuan Province and ecological data from 2006 to 2017, to explore the characters of TB and ecological factors, using the transfer function-noise model to forecast the trend of TB until 2035.

RESULTS

Factors affecting the incidence of TB, increasing per capita green area, reporting status of TB among Tibetans and Yi minorities, comprehensive treatment management, total cost of TB per capita for urban residents, proportion of males with high school education, 20 to 20 h of 24-h accumulated precipitation, reducing HIV at the same time as AIDS deaths, the increase in the proportion of males in junior high school education, and the increase in the number of registered TB cases can reduce the incidence of TB.

CONCLUSIONS

There was concentration mainly on enhanced control of the environment and society measures, helpful in guiding government planning to control TB. Reinforcement is required to reduce the TB of population aged 15-24 and aged 25-64 in socioeconomic level by 2035.

Challenge of ending TB in China: tuberculosis control in primary healthcare sectors under integrated TB control model-a systematic review and meta-analysis

BACKGROUND

China has the third-largest burden of tuberculosis (TB) cases in the world with great challenges towards ending TB. Primary health care (PHC) sectors play a critical role in TB prevention and control in communities under the Chinese integrated TB control model. However, there is a lack of comprehensive review of research evidence on TB control in PHC sectors under the integrated TB control model in China.

METHODS

This review was conducted following the PRISMA guidelines. Articles published from 2012 to January 2022 were searched from four international and three Chinese databases. Studies conducted inside mainland China and relevant with TB control service in PHC sectors under the integrated model were included. After study selection, data extraction, and quality assessment, the meta-analysis was performed with RevMan using a random-effect model.When I2 was more than 50%, subgroup analysis was performed to explore possible reasons for heterogeneity. We also conducted a post hoc sensitivity analysis for outcomes after meta-analysis by exclusion of studies with a high risk of bias or classified as low quality.

RESULTS

Forty-three studies from 16 provinces/municipalities in China were included in this review, and most studies included were of medium quality. PHC sectors in East China delivered TB control service better overall than that in West China, especially in tracing of patients and TB case management (TCM). In meta-analyses, both the pooled arrival rate of tracing and pooled TCM rate in East China were higher than those in West China. TB patients had a low degree of willingness to receive TCM provided by healthcare workers in PHC sectors nationwide, especially among migrant TB patients. There were 9 studies reporting factors related to TB control service in PHC sectors, 6 (2 in East and 4 in West China) of which indentified several characteristics of patients as associated factors. The context of PHC sectors was demonstrated to influence delivery of TB control service in PHC sectors in 5 studies (3 in East, 1 in Middle and 1 in West China). Most studies on strategies to promoting TB control services in PHC sectors were conducted in East China and some of these studies identified several online and offline interventions and strategies improving patients' treatment compliance [pooled OR (95% CI): 7.81 (3.08, 19.19] and awareness of TB [pooled OR (95% CI): 6.86 (2.16, 21.72)].

CONCLUSION

It is of urgent need to improve TB control in PHC sector in China, particularly in West China. Formative and implementation research with rigorous design are necessary to develop comprehensive, context-specific, and patient-centered TB control strategies to promote ending TB in China.

Spatiotemporal Distribution of Tuberculosis in the Oromia Region of Ethiopia: A Hotspot Analysis

Tuberculosis (TB) is a major public health concern in low- and middle-income countries including Ethiopia. This study aimed to assess the spatiotemporal distribution of TB and identify TB risk factors in Ethiopia's Oromia region. Descriptive and spatiotemporal analyses were conducted. Bayesian spatiotemporal modeling was used to identify covariates that accounted for variability in TB and its spatiotemporal distribution. A total of 206,278 new pulmonary TB cases were reported in the Oromia region between 2018 and 2022, with the lowest annual TB case notification (96.93 per 100,000 population) reported in 2020 (i.e., during the COVID-19 pandemic) and the highest TB case notification (106.19 per 100,000 population) reported in 2019. Substantial spatiotemporal variations in the distribution of notified TB case notifications were observed at zonal and district levels with most of the hotspot areas detected in the northern and southern parts of the region. The spatiotemporal distribution of notified TB incidence was positively associated with different ecological variables including temperature (β = 0.142; 95% credible interval (CrI): 0.070, 0.215), wind speed (β = -0.140; 95% CrI: -0.212, -0.068), health service coverage (β = 0.426; 95% CrI: 0.347, 0.505), and population density (β = 0.491; 95% CrI: 0.390, 0.594). The findings of this study indicated that preventive measures considering socio-demographic and health system factors can be targeted to high-risk areas for effective control of TB in the Oromia region. Further studies are needed to develop effective strategies for reducing the burden of TB in hotspot areas.

Spatial-temporal patterns and influencing factors for pulmonary tuberculosis transmission in China: an analysis based on 15 years of surveillance data

Profiting from a series of anti-tuberculosis programs in China, the number of tuberculosis (TB) cases has diminished dramatically in the past decades. However, long-term spatial-temporal variations, regional trends of prevalence, and mechanisms of determinant factors remain unclear. Age-period-cohort analysis and Bayesian space-time hierarchy statistics were conducted to identify high-risk populations and areas in mainland China, and the geographical detector model was used to evaluate the important drivers of the disease. The prevalence of pulmonary TB has declined from 73.3/100,000 in 2004 to 55.45/100,000 in 2018. A bimodal distribution was found in age groups, and the birth cohorts before 1978 had relative higher risk. The high-risk areas were mainly distributed in western China and south-central China, and several provinces in eastern China showed a potential increasing trend, including Beijing, Shanghai, Liaoning, and Guangdong province. The index of night light (Q = 0.46), the population density (Q = 0.41), PM10 (Q = 0.38), urbanization rate (Q = 0.32), and PM 2.5 (Q = 0.31) contributed substantially to the spatial distribution of pulmonary tuberculosis. The identifications of epidemic patterns, high-risk areas and influence factors would help design targeted intervention measures to achieve milestones of the end TB strategy.

Spatiotemporal associations between hand, foot and mouth disease and meteorological factors over multiple climate zones

Prior studies of hand, foot, and mouth disease (HFMD) have often observed inconsistent results regarding meteorological factors. We propose the hypothesis that these meteorological associations vary in regions because of the heterogeneity of their geographical characteristics. We have tested this hypothesis by applying a geographical detector and Bayesian space-time hierarchy model to measure stratified spatiotemporal heterogeneity and local associations between meteorological factors and HFMD risk in five climate zones in China from January 2016 to December 2017. We found a significant spatial stratified heterogeneity in HFMD risk and climate zone explained 15% of the spatial stratified heterogeneity. Meanwhile, there was a significant temporal stratified heterogeneity of 14% as determined by meteorological factors. Average temperatures and relative humidity had a significant positive effect on HFMD in all climate zones, they were the most obvious in the southern temperate zone. In northern temperate, southern temperate, northern subtropics, middle subtropics and southern subtropics climate zone, a 1 °C rise in temperature was related to an increase of 3.99%, 13.76%, 4.38%, 3.99%, and 7.74% in HFMD, and a 1% increment in relative humidity was associated with a 1.51%, 5.40%, 2.21%, 3.44%, and 4.78% increase, respectively. These findings provide strong support for our hypotheses that HFMD incidence has a significant spatiotemporal stratified heterogeneity and different climate zones have distinct influences on the disease. These findings provide strong support for our hypotheses: HFMD incidence had significant spatiotemporal stratified heterogeneity and different climate zones had distinct influences on it. The study suggested that HFMD prevention and policy should be made according to meteorological variation in each climate zone.

Spatial analysis of overweight prevalence in China: exploring the association with air pollution

BACKGROUND

Overweight is a known risk factor for various chronic diseases and poses a significant threat to middle-aged and elderly adults. Previous studies have reported a strong association between overweight and air pollution. However, the spatial relationship between the two remains unclear due to the confounding effects of spatial heterogeneity.

METHODS

We gathered height and weight data from the 2015 China Health and Retirement Long-term Survey (CHARLS), comprising 16,171 middle-aged and elderly individuals. We also collected regional air pollution data. We then analyzed the spatial pattern of overweight prevalence using Moran's I and Getis-Ord Gi* statistics. To quantify the explanatory power of distinct air pollutants for spatial differences in overweight prevalence across Southern and Northern China, as well as across different age groups, we utilized Geodetector's q-statistic.

RESULTS

The average prevalence of overweight among middle-aged and elderly individuals in each city was 67.27% and 57.39%, respectively. In general, the q-statistic in southern China was higher than that in northern China. In the north, the prevalence was significantly higher at 54.86% compared to the prevalence of 38.75% in the south. SO2 exhibited a relatively higher q-statistic in middle-aged individuals in both the north and south, while for the elderly in the south, NO2 was the most crucial factor (q = 0.24, p < 0.01). Moreover, fine particulate matter (PM2.5 and PM10) also demonstrated an important effect on overweight. Furthermore, we found that the pairwise interaction between various risk factors improved the explanatory power of the prevalence of overweight, with different effects for different age groups and regions. In northern China, the strongest interaction was found between NO2 and SO2 (q = 0.55) for middle-aged individuals and PM2.5 and SO2 (q = 0.27) for the elderly. Conversely, in southern China, middle-aged individuals demonstrated the strongest interaction between SO2 and PM10 (q = 0.60), while the elderly showed the highest interaction between NO2 and O3 (q = 0.42).

CONCLUSION

Significant spatial heterogeneity was observed in the effects of air pollution on overweight. Specifically, air pollution in southern China was found to have a greater impact on overweight than that in northern China. And, the impact of air pollution on middle-aged individuals was more pronounced than on the elderly, with distinct pollutants demonstrating significant variation in their impact. Moreover, we found that SO2 had a greater impact on overweight prevalence among middle-aged individuals, while NO2 had a greater impact on the elderly. Additionally, we identified significant statistically interactions between O3 and other pollutants.

Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

INTRODUCTION

The objective of this systematic review is to identify tuberculosis (TB) high-risk among the general population globally. The review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis.

METHODS

The studies included were those published in English, from original research, presented findings relevant to tuberculosis high-risk across the globe, published between 2017 and 2023, and were based on geospatial analysis of TB. Two reviewers independently selected the articles and were blinded to each other`s comments. The resultant disagreement was resolved by a third blinded reviewer. For bibliographic search, controlled and free vocabularies that address the question to be investigated were used. The searches were carried out on PubMed, LILACS, EMBASE, Scopus, and Web of Science. and Google Scholar.

RESULTS

A total of 79 published articles with a 40-year study period between 1982 and 2022 were evaluated. Based on the 79 studies, more than 40% of all countries that have carried out geospatial analysis of TB were from Asia, followed by South America with 23%, Africa had about 15%, and others with 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the high-risk and the factors that affect the hotspot's location are evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate-related clustering (15%), high-risk spread to neighbouring cities (13%), unstable and non-random cluster (11%).

CONCLUSION

There exist specific high-risk for TB which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policymakers. We recommend that more studies making use of spatial, temporal, and spatiotemporal analysis be carried out to point out territories and populations that are vulnerable to TB.

The incidence of tuberculous pleurisy in mainland China from 2005 to 2018

Background

Currently, tuberculous pleurisy (TP) remains a serious problem affecting global public health, including in China. Our purpose was to comprehensively understand and identify the incidence of TP in mainland China between 2005 and 2018.

Methods

The data on registered TP cases from 2005 to 2018 were acquired from the National Tuberculosis Information Management System. We analyzed the demographics, epidemiology, and time-space distribution of TP patients. Then, the effects of potentially influential factors on TP incidences, such as medical expenses per capita, GDP per capita, and population density, were assessed using the Spearman correlation coefficient.

Results

The incidence of TP increased in mainland China from 2005 to 2018, with a mean incidence of 2.5 per 100,000 population. Interestingly, spring was the peak season for TP, with more notified cases. Tibet, Beijing, Xinjiang, and Inner Mongolia had the highest mean annual incidence. A moderate positive relationship was found between TP incidence, medical expenses per capita, and GDP per capita.

Conclusions

The notified incidence of TP had an elevated trend from 2005 to 2018 in mainland China. The findings of this study provide insight into the knowledge of TP epidemiology in the country, which can help optimize resource allocation to reduce the TP burden.

Geographical evolutionary pathway of global tuberculosis incidence trends

BACKGROUNDS

Tuberculosis (TB) remains a serious public health and human development problem, especially in developing countries. Despite the effectiveness of directly observed therapy, short course programs in reducing transmission and progression of TB, poverty reduction and socioeconomic development remain crucial factors in decreasing TB incidence. However, the geographical pathway on the planet is not yet clear.

OBJECTIVES

This study was to reconstruct the geographical evolutionary process of TB in 173 countries and territories from 2010 to 2019 to analyze the socioeconomic determinants that impact the global TB epidemic. In addition, the TB incidence in 2030 was predicted.

METHODS

This study analyses TB incidence data from 173 countries and territories between 2010 and 2019. The Geotree model would be used to reconstruct the geographical evolutionary process of TB, which provides a simplified schema for geo-visualizing the trajectories of TB incidence and their socioeconomic drivers. Additionally, to estimate the future TB incidence in 2030, a multilevel model was utilized in conjunction with the hierarchical nature of the Geotree based on a stratified heterogeneity analysis.

RESULTS

Global TB incidence was found to be associated with the country type and development stages. Between 2010 and 2019, the average TB incidence rate in 173 countries and territories was -27.48%, with marked spatially stratified heterogeneity by country type and development stage. Low-income and lower-middle-income countries were most vulnerable to TB. Upper-middle-income countries experienced a faster decline in TB incidence than high-income countries, and TB incidence generally decreased as the development stage increased, except for the lower-middle development stage in 2019.The highest average rate of decline in TB incidence was observed in the upper-middle development stage of high-income countries, with a reduction of 45.24%. Meanwhile, 37 high-income countries in the high development stage demonstrated an average rate of change of -13.93%. Socioeconomic determinants, including gross domestic product per capita, urbanization rate, and sociodemographic index, were found to inhibit TB incidence. Based on current trends, the predicted average global TB incidence in 2030 is 91.581 per 100,000 population.

CONCLUSIONS

The trajectories of the global TB incidence have been reconstructed to formulate targeted public health responses. To eliminate TB, countries at similar development stage can draw on the experiences of countries at higher development stages that are tailored to their unique characteristics. By learning from successful TB control strategies, countries can take strategic steps toward eradicating TB and improving public health outcomes.

A Spatio-temporal Bayesian model to estimate risk and influencing factors related to tuberculosis in Chongqing, China, 2014-2020

BACKGROUND

Tuberculosis (TB) is a serious infectious disease that is one of the leading causes of death worldwide. This study aimed to investigate the spatial and temporal distribution patterns and potential influencing factors of TB incidence risk, and to provide a scientific basis for the prevention and control of TB.

METHODS

We collected reported cases of TB in 38 districts and counties in Chongqing from 2014 to 2020 and data on environment, population characteristics and economic factors during the same period. By constructing a Bayesian spatio-temporal model, we explored the spatio-temporal distribution pattern of TB incidence risk and potential influencing factors, identified key areas and key populations affected by TB, compared the spatio-temporal distribution characteristics of TB in populations with different characteristics, and explored the differences in the influence of various social and environmental factors.

RESULTS

The high-risk areas for TB incidence in Chongqing from 2014 to 2020 were mainly concentrated in southeastern and northeastern regions of Chongqing, and the overall relative risk (RR) of TB showed a decreasing trend during the study period, while RR of TB in main urban area and southeast of Chongqing showed an increasing trend. The RR of TB was relatively high in the main urban area for the female population and the population aged 0-29 years, and the RR of TB for the population aged 30-44 years in the main urban area and the population aged 60 years or older in southeast of Chongqing had an increasing trend, respectively. For each 1 μg/m³ increase in SO₂ and 1% increase in the number of low-income per 1000 non-agricultural households (LINA per 1000 persons), the RR of TB increased by 0.35% (95% CI: 0.08-0.61%) and 0.07% (95% CI: 0.05-0.10%), respectively. And LINA per 1000 persons had the greatest impact on the female population and the over 60 years old age group. Although each 1% increase in urbanization rate (UR) was associated with 0.15% (95% CI: 0.11-0.17%) reduction in the RR of TB in the whole population, the RR increased by 0.18% (95% CI: 0.16-0.21%) in the female population and 0.37% (95% CI: 0.34-0.45%) in the 0-29 age group.

CONCLUSION

This study showed that high-risk areas for TB were concentrated in the southeastern and northeastern regions of Chongqing, and that the elderly population was a key population for TB incidence. There were spatial and temporal differences in the incidence of TB in populations with different characteristics, and various socio-environmental factors had different effects on different populations. Local governments should focus on areas and populations at high risk of TB and develop targeted prevention interventions based on the characteristics of different populations.

Tuberculosis in older adults: case studies from four countries with rapidly ageing populations in the western pacific region

BACKGROUND

The Western Pacific Region has one of the fastest-growing populations of older adults (≥ 65 years) globally, among whom tuberculosis (TB) poses a particular concern. This study reports country case studies from China, Japan, the Republic of Korea, and Singapore reflecting on their experiences in managing TB among older adults.

FINDINGS

Across all four countries, TB case notification and incidence rates were highest among older adults, but clinical and public health guidance focused on this population was limited. Individual country reports illustrated a range of practices and challenges. Passive case finding remains the norm, with limited active case finding (ACF) programs implemented in China, Japan, and the Republic of Korea. Different approaches have been trialled to assist older adults in securing an early diagnosis, as well as adhering to their TB treatment. All countries emphasised the need for person-centred approaches that include the creative application of new technology and tailored incentive programs, as well as reconceptualisation of how we provide treatment support. The use of traditional medicines was found to be culturally entrenched among older adults, with a need for careful consideration of their complementary use. TB infection testing and the provision of TB preventive treatment (TPT) were underutilised with highly variable practice.

CONCLUSION

Older adults require specific consideration in TB response policies, given the burgeoning aging population and their high TB risk. Policymakers, TB programs and funders must invest in and develop locally contextualised practice guidelines to inform evidence-based TB prevention and care practices for older adults.

[The postal code as a "bar code" of antimicrobial resistance]

OBJECTIVE

The need to integrate local resistances into clinical practice is increasingly urgent, especially in Primary Care where empirical treatment is frequent.

METHODS

A retrospective observational study of positive microbiological isolates of Neisseria gonorrhoeae from any location (urethral, cervical, pharyngeal, rectal or urine) was carried out in the health area of Alcalá de Henares. Sociodemographic characteristics and resistance to cephalosporins, azithromycin, penicillin and quinolones were analyzed. Each isolate was related to its postal code of origin.

RESULTS

We analyzed 256 microbiological samples of N.gonorrhoeae, most of them male (92.9%) with a mean age of 33 years. Half of the samples (49.8%) were resistant to ciprofloxacin. Temporal and spatial evolution of antimicrobial resistance was integrated in heat maps.

CONCLUSIONS

Knowing local resistances can help to prescribe more adequate empirical treatments, especially in Primary Care, avoiding inadequate antibiotics and decreasing resistance rates.

Specific urban units identified in tuberculosis epidemic using a geographical detector in Guangzhou, China

Background

A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB’s spatial features and risk factors in urban areas remain poorly understood. This study aims to identify the spatial differentiations and potential influencing factors of TB in highly urbanized regions on a fine scale.

Methods

This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou, China. TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention. Before using Pearson correlation and a geographical detector (GD) to identify potential influencing factors, we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales.

Results

Owing to its strong spatial autocorrelation (Moran’s I = 0.33, Z = 4.71), the 2 km × 2 km grid was selected as the spatial scale. At this level, TB incidence was closely associated with most socioeconomic variables (0.31 < r < 0.76, P < 0.01). Of five environmental factors, only the concentration of fine particulate matter displayed significant correlation (r = 0.21, P < 0.05). Similarly, in terms of q values derived from the GD, socioeconomic variables had stronger explanatory abilities (0.08 < q < 0.57) for the spatial differentiation of the 2017 incidence of TB than environmental variables (0.06 < q < 0.27). Moreover, a much larger proportion (0.16 < q < 0.89) of the spatial differentiation was interpreted by pairwise interactions, especially those (0.60 < q < 0.89) related to the 2016 incidence of TB, officially appointed medical institutions, bus stops, and road density.

Conclusions

The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably influenced by several socioeconomic and environmental factors and their pairwise interactions on a fine scale. We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou. Our study provides helpful clues for local authorities implementing more effective intervention measures to reduce TB incidence in China’s municipal areas, which are featured by both a high degree of urbanization and a high incidence of TB.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-00967-z.