Space-time clustering and associated risk factors of pulmonary tuberculosis in southwest China

Pulmonary Tuberculosis Notification Rate Within Shenzhen, China, 2010-2019: Spatial-Temporal Analysis

BACKGROUND

Pulmonary tuberculosis (PTB) is a chronic communicable disease of major public health and social concern. Although spatial-temporal analysis has been widely used to describe distribution characteristics and transmission patterns, few studies have revealed the changes in the small-scale clustering of PTB at the street level.

OBJECTIVE

The aim of this study was to analyze the temporal and spatial distribution characteristics and clusters of PTB at the street level in the Shenzhen municipality of China to provide a reference for PTB prevention and control.

METHODS

Data of reported PTB cases in Shenzhen from January 2010 to December 2019 were extracted from the China Information System for Disease Control and Prevention to describe the epidemiological characteristics. Time-series, spatial-autocorrelation, and spatial-temporal scanning analyses were performed to identify the spatial and temporal patterns and high-risk areas at the street level.

RESULTS

A total of 58,122 PTB cases from 2010 to 2019 were notified in Shenzhen. The annual notification rate of PTB decreased significantly from 64.97 per 100,000 population in 2010 to 43.43 per 100,000 population in 2019. PTB cases exhibited seasonal variations with peaks in late spring and summer each year. The PTB notification rate was nonrandomly distributed and spatially clustered with a Moran I value of 0.134 (P=.02). One most-likely cluster and 10 secondary clusters were detected, and the most-likely clustering area was centered at Nanshan Street of Nanshan District covering 6 streets, with the clustering time spanning from January 2010 to November 2012.

CONCLUSIONS

This study identified seasonal patterns and spatial-temporal clusters of PTB cases at the street level in the Shenzhen municipality of China. Resources should be prioritized to the identified high-risk areas for PTB prevention and control.

Global and regional estimates of tuberculosis burden attributed to high fasting plasma glucose from 1990 to 2019: emphasis on earlier glycemic control

BACKGROUND

Previous studies have shown subjects suffering from diabetes or persistent hyperglycemia were more likely to develop tuberculosis (TB). However, the global burden of TB attributed to high fasting plasma glucose (HFPG) remains unclear. This study aimed to characterize the global, regional, and national TB burden attributed to HFPG from 1990 to 2019.

METHODS

With Global Burden of Disease study 2019, the numbers and age-standardized mortality rates (ASMR) and age-standardized disability-adjusted life years (DALY) rates (ASDR) of TB attributed to HFPG at global, regional, and national levels from 1990 to 2019 were extracted. The locally weighted regression model was applied to estimate the TB burden for different socio-demographic index (SDI) regions.

RESULTS

Globally, the ASMR and ASDR attributed to HFPG were 2.70 (95% UI, 1.64-3.94) and 79.70 (95% UI, 50.26-112.51) per 100,000 population in 1990, respectively. These rates decreased to 1.46 (95% UI, 0.91-2.08) and 45.53 (95% UI, 29.06-62.29) in 2019. The TB burden attributed to HFPG remained high in low SDI and Central Sub-Saharan Africa regions, while it declined with most significantly in high SDI and East Asia regions. Additionally, the ASMR and ASDR of TB attributed to HFPG were significantly higher in the male and the elderly population.

CONCLUSIONS

The global TB burden attributable to HFPG decreased from 1990 to 2019, but remained high in low SDI regions among high-risk populations. Thus, urgent efforts are required to enhance the awareness of early glycemic control and TB treatment to alleviate the severe situation.

Spatial and temporal clustering analysis of pulmonary tuberculosis and its associated risk factors in southwest China

Pulmonary tuberculosis (PTB) remains a serious public health problem, especially in areas of developing countries. This study aimed to explore the spatial-temporal clusters and associated risk factors of PTB in south-western China. Space-time scan statistics were used to explore the spatial and temporal distribution characteristics of PTB. We collected data on PTB, population, geographic information and possible influencing factors (average temperature, average rainfall, average altitude, planting area of crops and population density) from 11 towns in Mengzi, a prefecture-level city in China, between 1 January 2015 and 31 December 2019. A total of 901 reported PTB cases were collected in the study area and a spatial lag model was conducted to analyse the association between these variables and the PTB incidence. Kulldorff's scan results identified two significant space-time clusters, with the most likely cluster (RR = 2.24, p < 0.001) mainly located in northeastern Mengzi involving five towns in the time frame June 2017 - November 2019. A secondary cluster (RR = 2.09, p < 0.05) was located in southern Mengzi, covering two towns and persisting from July 2017 to December 2019. The results of the spatial lag model showed that average rainfall was associated with PTB incidence. Precautions and protective measures should be strengthened in high-risk areas to avoid spread of the disease.

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.

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.

Dose-response relationship between body mass index and tuberculosis in China: a population-based cohort study

OBJECTIVES

This study aimed to describe and quantify the relationship between body mass index (BMI) and tuberculosis (TB) incidence.

DESIGN

A population-based prospective cohort study.

SETTING

Ten randomly selected communities in the southwestern mountainous region of China.

PARTICIPANTS

Participants who had resided in study sites before screening for at least 6 months were eligible. Those who refused to participate or were temporary residents (who resided less than 6 months during three waves of screening) were excluded. The present research included 26 022 participants aged over 15 years for analyses.

INTERVENTIONS

The cohort study conducted three rounds of TB screening from 2013 to 2015. Face-to-face surveys for participants were carried out. TB symptoms positivity suspects underwent chest X-ray and sputum smear test for diagnosis.

PRIMARY OUTCOME MEASURES

The study outcome was the diagnosed active TB in the second and third rounds of screening.

RESULTS

During the follow-up of 2.25 years, 43 cases developed TB in 44 574.4 person-years. The negative log-linear relationship between BMI and TB incidence was fitted (adjusted R² =0.76). Overweight or obese was associated with a lower risk of TB compared with normal weight (adjusted HR (aHR) 0.34, 95% CI 0.14 to 0.82). The inverse log-linear associations between continuous BMI and individual TB risk were evaluated. In subgroup analysis, the risk of TB reduced 78% in overweight or obese women (aHR 0.22, 95% CI 0.05 to 0.97), and a 64% reduction in the elderly (aHR 0.36, 95% CI 0.12 to 1.00) compared with those with normal weight, respectively.

CONCLUSIONS

The study provided evidence for a negative association between BMI and TB development in Chinese adults. It suggests the inverse dose-response relationship between BMI and TB incidence, and implies an optimal cut-off point of BMI for screening strategy.

Influence of Public Health Services on the Goal of Ending Tuberculosis: Evidence From Panel Data in China

Background

The World Health Organization has proposed an initiative to “end tuberculosis (TB).” Unfortunately, TB continues to endanger the health of people worldwide. We investigated the impact of public health services (PHS) in China on TB incidence. In this way, we provided policy ideas for preventing the TB epidemic.

Methods

We used the “New Public Management Theory” to develop two indicators to quantify policy documents: multisector participation (MP) and the Assessable Public Health Service Coverage Rate (ASCR). The panel data from 31 provinces in Chinese mainland were collected from 2005 to 2019 based on 1,129 policy documents and the China Statistical Yearbook. A fixed-effect model was used to determine the impact of MP and the ASCR on TB incidence.

Results

From 2005 to 2019, the average MP increased from 89.25 to 97.70%, and the average ASCR increased from 53.97 to 78.40% in Chinese mainland. However, the development of ASCR between regions was not balanced, and the average level in the western region was lower than that in the eastern coastal provinces. With an increase in MP and the ASCR, the TB incidence had been decreasing gradually in recent years. The panel analysis results showed that MP (β = −0.76, p < 0.05). and ASCR (β = −0.40, p < 0.01) had a negative effect on TB incidence, respectively. Even if the control variables were added, the negative effects of MP (β = −0.86, p < 0.05) and ASCR (β = −0.35, p < 0.01) were still statistically significant.

Conclusions

Promoting the participation of multiple departments, as well as emphasizing the quality of PHS delivery, are important ways to alleviate the TB epidemic. The settings of evaluation indices for PHS provision should be strengthened in the future.

The Spatial Distribution of Pulmonary Tuberculosis in Kabanjahe District, Karo Regency, Indonesia

BACKGROUND: Tuberculosis is an infectious disease and global concern today. AIM: This study aims to map the incidence of pulmonary tuberculosis risk factors in Kabanjahe District, Karo Regency. METHOD: This research is an ecological study with a case-control study design. This research was conducted in Kabanjahe District in January - October 2020. All people who checked and declared to have tuberculosis based on clinical symptoms to be the population in this study. The sample size was calculated with a minimum sample size of 58 for the case group and 58 for the control group with a ratio of 1:1. The distribution pattern of pulmonary tuberculosis and environmental risk factors with the incidence of tuberculosis was carried out using a Geographic Information System (GIS) to determine the distribution of cases. Spatial analysis used average nearest neighbor, overlay and buffer followed with logistic regression as multivariate statistical analysis. RESULT:  The distribution pattern of pulmonary tuberculosis in Kabanjahe District tends to group (clusters). GeoDa software found the relationship between population density and tuberculosis incidence in Kabanjahe District with p values 0.04. There is a relationship between income, ventilation, floor conditions, humidity, and lighting with the incidence of tuberculosis. Humidity is the most dominant variable associated with the incidence of tuberculosis.   CONCLUSION: The incidence of tuberculosis cases in Kabanjahe District is dominantly influenced by the humidity factor of the house which is increasingly at risk due to poor ventilation, unstable room temperature, and bad circulation.

Spatiotemporal Patterns of Tuberculosis in Hunan Province, China

Tuberculosis (TB) is the leading cause of death from a bacterial pathogen worldwide. China has the third highest TB burden in the world, with a high reported burden in Hunan Province (amongst others). This study aimed to investigate the spatial distribution of TB and identify socioeconomic, demographic, and environmental drivers in Hunan Province, China. Numbers of reported cases of TB were obtained from the Tuberculosis Control Institute of Hunan Province, China. A wide range of covariates were collected from different sources, including from the Worldclim database, and the Hunan Bureau of Statistics. These variables were summarized at the county level and linked with TB notification data. Spatial clustering of TB was explored using Moran’s I statistic and the Getis–Ord statistic. Poisson regression models were developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian approach with Markov chain Monte Carlo (MCMC) simulation. A total of 323,340 TB cases were reported to the Hunan TB Control Institute from 2013 to 2018. The mean age of patients was 51.7 years (SD + 17.6 years). The majority of the patients were male (72.6%, n = 234,682) and had pulmonary TB (97.5%, n = 315,350). Of 319,825 TB patients with registered treatment outcomes, 306,107 (95.7%) patients had a successful treatment outcome. The annual incidence of TB decreased over time from 85.5 per 100,000 population in 2013 to 76.9 per 100,000 population in 2018. TB case numbers have shown seasonal variation, with the highest number of cases reported during the end of spring and the beginning of summer. Spatial clustering of TB incidence was observed at the county level, with hotspot areas detected in the west part of Hunan Province. The spatial clustering of TB incidence was significantly associated with low sunshine exposure (RR: 0.86; 95% CrI: 0.74, 0.96) and a low prevalence of contraceptive use (RR: 0.88; 95% CrI: 0.79, 0.98). Substantial spatial clustering and seasonality of TB incidence were observed in Hunan Province, with spatial patterns associated with environmental and health care factors. This research suggests that interventions could be more efficiently targeted at locations and times of the year with the highest transmission risk.

Population aging and trends of pulmonary tuberculosis incidence in the elderly

BACKGROUND

To explore population aging and the epidemic trend of pulmonary tuberculosis (PTB) in the elderly, and provide a basis for the prevention and control of pulmonary tuberculosis among the elderly.

METHODS

We collected clinical information of 239,707 newly active PTB patients in Shandong Province from 2005 to 2017. We analyzed and compared the clinical characteristics, reported incidence and temporal trend of PTB among the elderly group (≥60 years) and the non-elderly group (< 60 years) through logistic model and Join-point regression model.

RESULTS

Among the total PTB cases, 77,192(32.2%) were elderly. Compared with non-elderly patients, newly active elderly PTB patients account for a greater proportion of male cases (OR 1.688, 95% CI 1.656-1.722), rural population cases (OR 3.411, 95% CI 3.320-3.505) and bacteriologically confirmed PTB cases (OR 1.213, 95%CI 1.193-1.234). The annual reported incidence of total, elderly, pulmonary bacteriologically confirmed cases were 35.21, 68.84, 35.63 (per 100,000), respectively. The annual reported incidence of PTB in the whole population, the elderly group and the non-elderly group has shown a slow downward trend since 2008. The joinpoint regression model showed that the overall reported incidence of PTB in the elderly significantly decreased from 2007 to 2017 (APC = -5.3, P < 0.05). The reported incidence of bacteriologically confirmed PTB among elderly patients declined rapidly from 2005 to 2014(2005-2010 APC = -7.2%, P < 0.05; 2010-2014 APC = -22.6%, P < 0.05; 2014-2017 APC = -9.0%, P = 0.1). The reported incidence of clinically diagnosed PTB among elderly patients from 2005 to 2017 (11.48-38.42/100,000) increased by about 235%. It rose significantly from 2007 to 2014 (APC = 9.4, P<0.05).

CONCLUSIONS

Compared with the non-elderly population, the reported incidence of PTB in the elderly population is higher. The main burden of PTB will shift to the elderly, men, rural population, and clinically diagnosed patients. With the intensification of aging, more researches on elderly PTB prevention and treatment will facilitate the realization of the global tuberculosis (TB) control targets.

SARS-CoV-2 Molecular Transmission Clusters and Containment Measures in Ten European Regions during the First Pandemic Wave

Background: The spatiotemporal profiling of molecular transmission clusters (MTCs) using viral genomic data can effectively identify transmission networks in order to inform public health actions targeting SARS-CoV-2 spread. Methods: We used whole genome SARS-CoV-2 sequences derived from ten European regions belonging to eight countries to perform phylogenetic and phylodynamic analysis. We developed dedicated bioinformatics pipelines to identify regional MTCs and to assess demographic factors potentially associated with their formation. Results: The total number and the scale of MTCs varied from small household clusters identified in all regions, to a super-spreading event found in Uusimaa-FI. Specific age groups were more likely to belong to MTCs in different regions. The clustered sequences referring to the age groups 50–100 years old (y.o.) were increased in all regions two weeks after the establishment of the lockdown, while those referring to the age group 0–19 y.o. decreased only in those regions where schools’ closure was combined with a lockdown. Conclusions: The spatiotemporal profiling of the SARS-CoV-2 MTCs can be a useful tool to monitor the effectiveness of the interventions and to reveal cryptic transmissions that have not been identified through contact tracing.

Spatial-temporal analysis of tuberculosis in Chongqing, China 2011-2018

BACKGROUND

China is a country with a high burden of pulmonary tuberculosis (PTB). Chongqing is in the southwest of China, where the notification rate of PTB ranks tenth in China. This study analyzed the temporal and spatial distribution characteristics of PTB in Chongqing in order to improve TB control measures.

METHODS

A spatial-temporal analysis has been performed based on the data of PTB from 2011 to 2018, which was extracted from the National Surveillance System. The effect of TB control was measured by variation trend of pathogenic positive PTB notification rate and total TB notification rate. Time series, spatial autonomic correlation and spatial-temporal scanning methods were used to identify the temporal trends and spatial patterns at county level.

RESULTS

A total of 188,528 cases were included in this study. A downward trend was observed in PTB between 2011 and 2018 in Chongqing. The peak of PTB notification occurred in late winter and early spring annually. By calculating the value of Global Moran's I and Local Getis's Gi*, we found that PTB was spatially clustered and some significant hot spots were detected in the southeast and northeast of Chongqing. One most likely cluster and three secondary clusters were identified by Kulldorff's scan spatial-temporal Statistic.

CONCLUSIONS

This study identified seasonal patterns and spatial-temporal clusters of PTB cases in Chongqing. Priorities should be given to southeast and northeast of Chongqing for better TB control.

Spatio-temporal analysis of socio-economic characteristics for pulmonary tuberculosis in Sichuan province of China, 2006-2015

Background

The disease burden caused by pulmonary tuberculosis (TB) in Sichuan province still persisted at a high level, and large spatial variances were presented across regional distribution disparities. The socio-economic factors were suspected to affect the population of TB notification, we aimed to describe TB case notification rate (CNR) and identify which factors influence TB epidemic are necessary for the prevention and control of the disease in Sichuan province.

Methods

A retrospective cross-sectional study and an ecological spatial analysis was conducted to quantify the presence and location of spatial clusters of TB by the Moran’s I index and examined these patterns with socio-economic risk factors by hierarchical Bayesian spatio-temporal model.

Results

A total of 630,009 pulmonary TB cases were notified from 2006 to 2015 in 181 counties of Sichuan province. The CNR decreased year by year since 2007, from 88.70 to 61.37 per 100,000 persons. The spatial heterogeneities of CNR were observed during the study periods. Global Moran’s I index varied from 0.23 to 0.44 with all P-value < 0.001. The Bayesian spatio-temporal model with parametric spatio-temporal interactions was chosen as the best model according to the minimum of Deviance Information Criterion (DIC)(19,379.01), and in which the quadratic form of time was taken. The proportion of age group and education year were all associated with CNR after adjusting the spatial effect, temporal effect and spatio-temporal interactions. TB CNR increased by 10.2% [95% credible interval (CI): 6.7–13.7%] for every 1-standard-deviation increase in proportion of age group and decreased by 23% (95% CI: 13.7–32.7%) for every 1-standard-deviation increase in education year.

Conclusions

There were spatial clusters of TB notification rate in Sichuan province from 2006 to 2015, and heavy TB burden was mainly attributed to aging and low socioeconomic status including poor education. Thus, it is more important to pay more attention to the elderly population and improve socioeconomic status including promoting education level in Sichuan province to reduce the TB burden.

Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014-2018

Although immunization against varicella using vaccines has been proven to be significant and effective in the past decades, varicella remains a major public health concern for many developing countries. Varicella vaccination has not been introduced into routine immunization programs in China, and varicella outbreaks have continued to occur. Taking the city of Chongqing, which has a high prevalence of varicella, as an example, this study explored the spatiotemporal epidemiology of varicella. Based on the reported data of varicella cases from 1 January 2014 to 31 December 2018 in Chongqing, hot spots and space-time clusters of varicella were identified using spatial autocorrelation analysis and scan statistics. Within this period, a total of 112,273 varicella cases were reported in Chongqing (average annual incidence: 73.44 per 100,000), including one death. The incidence of varicella showed an increasing trend with significant seasonal peaks, which occurred during April to July and October to January of the following year. The total ratio of male to female patients affected was 1.10:1. Children under the age of 15 and students accounted for the majority of the patient population. The hotspots detected through local spatial autocorrelation analysis, and the most likely clusters identified by scan analysis, were primarily in the main urban districts of Chongqing. The secondary clusters were mostly detected in northeast and southwest Chongqing. There were obvious spatial dependence and spatiotemporal clustering characteristics of varicella in Chongqing from 2014 to 2018. High-risk districts, populations, and peak periods were found in this study, which could be helpful in implementing varicella prevention and control programs, and in adjusting vaccination strategies for the varicella vaccine based on actual conditions.

The characteristics of spatial-temporal distribution and cluster of tuberculosis in Yunnan Province, China, 2005-2018

BACKGROUND

Tuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. Meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS.

METHODS

Data for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff's space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS.

RESULT

There were a total of 381,855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100,000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR = 2.6, P < 0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS.

CONCLUSION

This study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control.

The spatio-temporal analysis of the incidence of tuberculosis and the associated factors in mainland China, 2009-2015

BACKGROUND

Tuberculosis is still one of the most infectious diseases in China. This study aimed to explore the spatio-temporal distribution of TB and the associated factors in mainland China from 2009 to 2015.

METHODS

A Bayesian spatio-temporal model was utilized to analyse the correlation of socio-economic, healthcare, demographic and meteorological factors with the population level number of TB.

RESULTS

The Bayesian spatio-temporal analysis showed that for the population level number of TB, the estimated parameters of the ratio of males to females, the number of beds in medical institutions, the population density, the proportion of the population that is rural, the amount of precipitation, the largest wind speed and the sunshine duration were 0.556, 0.197, 0.199, 29.03,0.1958, 0.0854 and 0.2117, respectively, demonstrating positive associations. However, health personnel, per capita annual gross domestic product, minimum temperature and humidity indicated negative associations, and the corresponding parameters were -0.050, -0.095, -0.0022 and -0.0070, respectively.

CONCLUSIONS

Socio-economic, number of health personnel, demographic and meteorological factors could affect the case notification number of TB to different degrees and in different directions.