Spatiotemporal epidemiology of, and factors associated with, the tuberculosis prevalence in northern China, 2010-2014

Spatial autocorrelation with environmental factors related to tuberculosis prevalence in Nepal, 2020-2023

BACKGROUND

Despite global efforts to reduce tuberculosis (TB) incidence, Nepal remains burdened by approximately 70,000 new cases annually, with an incidence rate of 229 per 100,000 people in 2022. This study investigated the geographic patterns of TB notifications in Nepal from fiscal year 2020 to 2023, focusing on environmental determinants such as land surface temperature (LST), urbanization, precipitation and cropland coverage.

METHODS

This study examined the spatial association between environmental factors and TB prevalence in Nepal at the district level, utilizing Geographic Information System (GIS) techniques, bivariate Local Indicators of Spatial Association (LISA) and spatial regression analyses. The tuberculosis prevalence data were obtained from the National Tuberculosis Control Center (NTCC) Nepal for the fiscal years (FY) 2020-2023.

RESULTS

Over the three fiscal years, high TB prevalence consistently clustered in districts such as Banke, Parsa, and Rautahat, while low prevalence areas included Mustang and Kaski. Significant positive spatial autocorrelation was found between environmental factors and TB prevalence. Moran's I values were as follows: for LST (day), 0.379, 0.424, and 0.423; for LST (night), 0.383, 0.420, and 0.425; for cropland coverage, 0.325, 0.339, and 0.373; for urbanization, 0.197, 0.245, and 0.246; and for precipitation, 0.222, 0.349, and 0.104 across FY 2020-2021, FY 2021-2022 and FY 2022-2023, respectively. Regression analyses, including Ordinary Least Squares (OLS), Spatial Lag Model (SLM), and Spatial Error Model (SEM), demonstrated that Land Surface Temperature Night (LSTN), urbanization, and precipitation significantly influenced TB prevalence, explaining up to 72.1% of the variance in FY 2021-2022 (R2: 0.721).

CONCLUSIONS

Environmental factors significantly influence the spatial distribution of TB in Nepal. This underscores the importance of integrating disease management strategies with environmental health policies in effectively addressing TB prevalence.

Predicting Tuberculosis Risk in Cattle, Buffaloes, Sheep, and Goats in China Based on Air Pollutants and Meteorological Factors

Tuberculosis is a zoonotic chronic respiratory infectious disease caused by the Mycobacterium tuberculosis complex. The outbreak and epidemic of tuberculosis can seriously threaten human and veterinary health. To investigate the effects of environmental factors on tuberculosis in domestic ruminants, we collected data regarding the prevalence of tuberculosis in cattle, buffaloes, sheep, and goats in China (1956-2024) from publicly published literature and available databases. We identified the key risk factors among six major air pollutants and 19 bioclimatic variables; simulated the risk distribution of tuberculosis in cattle, buffaloes, sheep, and goats in China using the maximum entropy ecological niche model; and evaluated the effects of environmental factors. The area under the curve of the model was 0.873 (95% confidence interval, 0.851-0.895). The risk factors that most significantly influenced the prevalence of tuberculosis were the nitrogen dioxide (NO2) level, mean temperature of the coldest quarter, cattle distribution density, sheep distribution density, ozone (O3) level, and precipitation of the driest month. The predicted map of tuberculosis risk in cattle, buffaloes, sheep, and goats indicated that the high-risk regions were mainly distributed in South, North, East, and Northwest China. Improved surveillance is needed in these high-risk areas, and early preventive measures must be implemented based on the risk factors identified to reduce the future prevalence of tuberculosis in cattle, buffaloes, sheep, and goats.

Ecological-level factors associated with tuberculosis incidence and mortality: A systematic review and meta-analysis

Globally, tuberculosis (TB) is the leading infectious cause of morbidity and mortality, with the risk of infection affected by both individual and ecological-level factors. While systematic reviews on individual-level factors exist, there are currently limited studies examining ecological-level factors associated with TB incidence and mortality. This study was conducted to identify ecological factors associated with TB incidence and mortality. A systematic search for analytical studies reporting ecological factors associated with TB incidence or mortality was conducted across electronic databases such as PubMed, Embase, Scopus, and Web of Science, from each database's inception to October 30, 2023. A narrative synthesis of evidence on factors associated with TB incidence and mortality from all included studies, alongside random-effects meta-analysis where applicable, estimated the effects of each factor on TB incidence. A total of 52 articles were included in the analysis, and one study analysed two outcomes, giving 53 studies. Narrative synthesis revealed predominantly positive associations between TB incidence and factors such as temperature (10/18 studies), precipitation (4/6), nitrogen dioxide (6/9), poverty (4/4), immigrant population (3/4), urban population (3/8), and male population (2/4). Conversely, air pressure (3/5), sunshine duration (3/8), altitude (2/4), gross domestic product (4/9), wealth index (2/8), and TB treatment success rate (2/2) mostly showed negative associations. Particulate matter (1/1), social deprivation (1/1), and population density (1/1) were positively associated with TB mortality, while household income (2/2) exhibited a negative association. In the meta-analysis, higher relative humidity (%) (relative risk (RR) = 1.45, 95%CI:1.12, 1.77), greater rainfall (mm) (RR = 1.56, 95%CI: 1.11, 2.02), elevated sulphur dioxide (μg m-3) (RR = 1.04, 95% CI:1.01, 1.08), increased fine particulate matter concentration (PM2.5) (μg/ m3) (RR = 1.33, 95% CI: 1.18, 1.49), and higher population density (people/km2) (RR = 1.01,95%CI:1.01-1.02) were associated with increased TB incidence. Conversely, higher average wind speed (m/s) (RR = 0.89, 95%CI: 0.82,0.96) was associated with decreased TB incidence. TB incidence and mortality rates were significantly associated with various climatic, socioeconomic, and air quality-related factors. Intersectoral collaboration across health, environment, housing, social welfare and economic sectors is imperative for developing integrated approaches that address the risk factors associated with TB incidence and mortality.

Epidemiological characteristics of tuberculosis incidence and its macro-influence factors in Chinese mainland during 2014-2021

BACKGROUND

Tuberculosis (TB) remains a pressing public health issue, posing a significant threat to individuals' well-being and lives. This study delves into the TB incidence in Chinese mainland during 2014-2021, aiming to gain deeper insights into their epidemiological characteristics and explore macro-level factors to enhance control and prevention.

METHODS

TB incidence data in Chinese mainland from 2014 to 2021 were sourced from the National Notifiable Disease Reporting System (NNDRS). A two-stage distributed lag nonlinear model (DLNM) was constructed to evaluate the lag and non-linearity of daily average temperature (℃, Atemp), average relative humidity (%, ARH), average wind speed (m/s, AWS), sunshine duration (h, SD) and precipitation (mm, PRE) on the TB incidence. A spatial panel data model was used to assess the impact of demographic, medical and health resource, and economic factors on TB incidence.

RESULTS

A total of 6,587,439 TB cases were reported in Chinese mainland during 2014-2021, with an average annual incidence rate of 59.17/100,000. The TB incidence decreased from 67.05/100,000 in 2014 to 46.40/100,000 in 2021, notably declining from 2018 to 2021 (APC = -8.87%, 95% CI: -11.97, -6.85%). TB incidence rates were higher among males, farmers, and individuals aged 65 years and older. Spatiotemporal analysis revealed a significant cluster in Xinjiang, Qinghai, and Xizang from March 2017 to June 2019 (RR = 3.94, P < 0.001). From 2014 to 2021, the proportion of etiologically confirmed cases increased from 31.31% to 56.98%, and the time interval from TB onset to diagnosis shortened from 26 days (IQR: 10-56 days) to 19 days (IQR: 7-44 days). Specific meteorological conditions, including low temperature (< 16.69℃), high relative humidity (> 71.73%), low sunshine duration (< 6.18 h) increased the risk of TB incidence, while extreme low wind speed (< 2.79 m/s) decreased the risk. The spatial Durbin model showed positive associations between TB incidence rates and sex ratio (β = 1.98), number of beds in medical and health institutions per 10,000 population (β = 0.90), and total health expenses (β = 0.55). There were negative associations between TB incidence rates and population (β = -1.14), population density (β = -0.19), urbanization rate (β = -0.62), number of medical and health institutions (β = -0.23), and number of health technicians per 10,000 population (β = -0.70).

CONCLUSIONS

Significant progress has been made in TB control and prevention in China, but challenges persist among some populations and areas. Varied relationships were observed between TB incidence and factors from meteorological, demographic, medical and health resource, and economic aspects. These findings underscore the importance of ongoing efforts to strengthen TB control and implement digital/intelligent surveillance for early risk detection and comprehensive interventions.

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.

Spatiotemporal Changes in Pulmonary Tuberculosis Incidence in a Low-Epidemic Area of China in 2005-2020: Retrospective Spatiotemporal Analysis

BACKGROUND

In China, tuberculosis (TB) is still a major public health problem, and the incidence of TB has significant spatial heterogeneity.

OBJECTIVE

This study aimed to investigate the temporal trends and spatial patterns of pulmonary tuberculosis (PTB) in a low-epidemic area of eastern China, Wuxi city, from 2005 to 2020.

METHODS

The data of PTB cases from 2005 to 2020 were obtained from the Tuberculosis Information Management System. The joinpoint regression model was used to identify the changes in the secular temporal trend. Kernel density analysis and hot spot analysis were used to explore the spatial distribution characteristics and clusters of the PTB incidence rate.

RESULTS

A total of 37,592 cases were registered during 2005-2020, with an average annual incidence rate of 34.6 per 100,000 population. The population older than 60 years had the highest incidence rate of 59.0 per 100,000 population. In the study period, the incidence rate decreased from 50.4 to 23.9 per 100,000 population, with an average annual percent change of -4.9% (95% CI -6.8% to -2.9%). The incidence rate of pathogen-positive patients increased during 2017-2020, with an annual percent change of 13.4% (95% CI 4.3%-23.2%). The TB cases were mainly concentrated in the city center, and the incidence of hot spots areas gradually changed from rural areas to urban areas during the study period.

CONCLUSIONS

The PTB incidence rate in Wuxi city has been declining rapidly with the effective implementation of strategies and projects. The populated urban centers will become key areas of TB prevention and control, especially in the older population.

A study of risk factors for tuberculous meningitis among patients with tuberculosis in China: An analysis of data between 2012 and 2019

Purpose

The present study aimed to explore the risk factors for tuberculous meningitis (TBM) among patients with tuberculosis (TB).

Methods

This retrospective study was conducted on patients with TB who were hospitalized in Beijing Chest Hospital between January 2012 and December 2019. Demographic and clinical data of patients with TB were extracted from electronic medical records using a standardized data collection system. Logistic regression was used to analyze the risk factors associated with TBM.

Results

Of the total number of 22,988 cases enrolled, 3.1% were cases of TBM, which included 127 definite and 581 probable TBM, respectively. Multivariate analysis showed that definite TBM was significantly associated with patients aged < 30 years [adjusted odds ratio (aOR) = 3.015, 95% confidence interval (CI): (1.451-6.266)], who were farmers [aOR = 1.490, 95%CI: (1.020-2.177)], with miliary pulmonary TB [aOR = 105.842, 95%CI: (71.704-156.235)], and with malnutrition [aOR = 2.466, 95%CI: (1.110-5.479)]. Additionally, probable TBM was significantly associated with patients aged < 30 years [aOR = 2.174, 95% CI: (1.450-3.261)], aged 30-59 years [aOR = 1.670, 95% CI: (1.222-2.282)], who were farmers [aOR = 1.482, 95%CI: (1.203-1.825)], with miliary pulmonary TB [aOR = 108.696, 95%CI: (87.122-135.613)], and with a digestive system TB [aOR = 2.906, 95%CI: (1.762-4.793)].

Conclusion

An age of < 30 years, being a farmer, and having miliary pulmonary TB were risk factors for TBM among patients with TB. Further screening of patients with TB with aforementioned characteristics could facilitate clinicians to identify patients with TBM at an early stage.

Spatial Co-Clustering of Tuberculosis and HIV in Ethiopia

Background: Tuberculosis (TB) and HIV are epidemiologically associated, and their co-dynamics suggest that the two diseases are directly related at the population level and within the host. However, there is no or little information on the joint spatial patterns of the two diseases in Ethiopia. The main objective of the current study was to assess the spatial co-clustering of TB and HIV cases simultaneously in Ethiopia at the district level. Methods: District-level aggregated data collected from the national Health Management Information System (HMIS) for the years 2015 to 2018 on the number of TB cases enrolled in directly observed therapy, short course (DOTS) who were tested for HIV and the number of HIV patients enrolled in HIV care who were screened for TB during their last visit to health care facilities were used in this study. The univariate and bivariate global and local Moran’s I indices were applied to assess the spatial clustering of TB and HIV separately and jointly. Results: The results of this study show that the two diseases were significantly (p-value <0.001) spatially autocorrelated at the district level with minimum and maximum global Moran’s I values of 0.407 and 0.432 for TB, 0.102 and 0.247 for HIV, and 0.152 and 0.251 for joint TB/HIV. The district-level TB/HIV spatial co-clustering patterns in Ethiopia in most cases overlapped with the hot spots of TB and HIV. The TB/HIV hot-spot clusters may appear due to the observed high TB and HIV prevalence rates in the hot-spot districts. Our results also show that there were low-low TB/HIV co-clusters or cold spots in most of the Afar and Somali regions, which consistently appeared for the period 2015−2018. This may be due to very low notifications of both diseases in the regions. Conclusions: This study expanded knowledge about TB and HIV co-clustering in Ethiopia at the district level. The findings provide information to health policymakers in the country to plan geographically targeted and integrated interventions to jointly control TB and HIV.

Contributions of ambient temperature and relative humidity to the risk of tuberculosis admissions: A multicity study in Central China

BACKGROUND

As a communicable disease and major public health issue, many studies have quantified the associations between tuberculosis (TB) and meteorological factors with inconsistent results. The purpose of this multicenter study was to characterize the associations between ambient temperature, humidity and the risk of TB hospitalizations and to investigate potential heterogeneity.

METHOD

Data on daily hospitalizations for TB, meteorological factors and ambient air pollutants for 16 cities in Anhui Province were collected from 2015 to 2020. A distributed lag nonlinear model (DLNM) was performed to obtain the estimates of meteorological-TB relationships by cities. Then, we used the multivariate meta-regression model to pool the city-specific estimates with air pollution, demographic indicators, medical resource and latitude as potential modifiers to explore the sources of heterogeneity. Finally, we divided the whole province into three regions to validate the meteorological-TB relationships by regions.

RESULTS

The overall pooled temperature-TB association presented an approximate S-shaped curve, with relative risk (RR) peaking at 5 °C (RR = 1.536, 95% CI: 1.303-1.811) compared to the reference temperature (27 °C). Lag-response curve suggested that low temperature exposure increased the risk of TB hospitalizations at lag 0 and 1 day (lag0 day: RR = 1.136, 95% CI: 1.048-1.231, lag1 day: RR = 1.052, 95% CI: 1.023-1.082). However, the overall exposure-response curve between relative humidity and TB showed almost horizontal line with reference relative humidity to 78%. The residual heterogeneity ranged from 27.1% to 36.9%, with air pollution, latitude and medical resource explained the largest proportion.

CONCLUSION

We found that low temperature exposure is associated with an acute increased risk of TB hospitalizations in Anhui Province. The association between temperature and TB admission varies depending on air pollution, latitude, and medical resources. Since the effect of short-term exposure to humidity is not significant, further studies are supposed to focus on the long-term effect of humidity.

Association between averaged meteorological factors and tuberculosis risk: A systematic review and meta-analysis

Inconsistencies were discovered in the findings regarding the effects of meteorological factors on tuberculosis (TB). This study conducted a systematic review of published studies on the relationship between TB and meteorological factors and used a meta-analysis to investigate the pooled effects in order to provide evidence for future research and policymakers. The literature search was completed by August 3rd, 2021, using three databases: PubMed, Web of Science and Embase. Relative risks (RRs) in included studies were extracted and all effect estimates were combined together using meta-analysis. Subgroup analyses were carried out based on the resolution of exposure time, regional climate, and national income level. A total of eight studies were included after screening for inclusion and exclusion criteria. Our results show that TB risk was positively correlated with precipitation (RR = 1.32, 95% CI: 1.14, 1.51), while temperature (RR = 1.15, 95% CI: 1.00, 1.32), humidity (RR = 1.05, 95% CI: 0.99, 1.10), air pressure (RR = 0.89, 95% CI: 0.69, 1.14) and sunshine duration (RR = 0.95, 95% CI: 0.80, 1.13) all had no statistically significant correlation. Subgroup analysis shows that quarterly measure resolution, low and middle Human Development Index (HDI) level and subtropical climate increase TB risk not only in precipitation, but also in temperature and humidity. Moreover, less heterogeneity was observed in "high and extremely high" HDI areas and subtropical areas than that in other subgroups (I² = 0%). Precipitation, a subtropical climate, and a low HDI level are all positive influence factors to tuberculosis. Therefore, residents and public health managers should take precautionary measures ahead of time, especially in extreme weather conditions.

Childhood Tuberculosis in Mongolia: Trends and Estimates, 2010-2030

Mongolia was listed among the 30 countries with a high tuberculosis burden in 2021. Approximately 10-11% of the tuberculosis cases are of children, which is higher than the global average (6.0%). As children are a vulnerable population, it is important to understand the current situation and prioritize the development of tuberculosis prevention strategies. However, only few studies have addressed childhood tuberculosis in Mongolia. Therefore, we aimed to describe the characteristics of childhood tuberculosis and to show its trends and estimates in Mongolia. We performed descriptive and trend analyses on secondary data from the National Center for Communicable Diseases from 2010 to 2020. A total of 4,242 childhood tuberculosis cases, compiled from nine districts of the capital city and 21 provinces, were analyzed. We found that tuberculosis occurred more frequently in school-age children, and 71.8% of the all cases were an extrapulmonary tuberculosis. Trend analysis revealed that childhood tuberculosis continuously increased with fluctuations from 2018 onwards. The central region, including the capital city of Ulaanbaatar, is the most tuberculosis-burdened. Childhood tuberculosis is estimated to increase in the central region and decrease in the others from 2021 to 2030. Our findings showed that the national childhood tuberculosis trend is increasing, although there are differences in the pattern between regions. Further studies are needed to identify the determinant factors of regional differences, and age-specific public health interventions, such as scale-up screening and preventive treatment, are in demand in high-prevalence areas.

Variation of tuberculosis prevalence across diagnostic approaches and geographical areas of Indonesia

Background

Tuberculosis (TB) has contributed to a significant disease burden and economic loss worldwide. Given no gold standard for diagnosis, early identification of TB infection has been challenging. This study aimed to comparatively investigate the prevalence of TB across diagnostic approaches (sputum AFB, sputum culture, sputum genetic test, and chest x-ray) and geographical areas of Indonesia.

Methods

Participant demographic variables and TB screening test results were obtained from the Tuberculosis Unit, Health Research and Development Agency, Ministry of Health (HRDA-MoH). The prevalence of pulmonary TB in populations aged 15 years and over was calculated using TB cases as a numerator and populations aged 15 years and over as a denominator. Variations across geographical areas and diagnostic approaches were expressed as prevalence and 95% confidence interval (CI).

Results

A total of 67,944 records were reviewed. Based on bacteriological evidence, the prevalence of TB per 100,000 in Indonesia was 759 (95% CI: 589.7–960.8) with variations across areas: 913 (95% CI 696.7–1,176.7; Sumatra), 593 (95% CI 447.2–770.6; Java-Bali), and 842 (95% CI 634.7–1,091.8; other islands). Also, the prevalence of TB varied across diagnostic approaches: 256.5 (sputum AFB), 545 (sputum culture), 752.2 (chest x-ray), and 894.9 (sputum genetic test). Based on sputum AFB, the TB prevalence varied from 216.6 (95% CI 146.5–286.8; Java-Bali), 259.9 (95% CI 184.2–335.6; other islands) to 307.4 (95% CI 208.3–406.5; Sumatra). Based on sputum culture, the TB prevalence ranged from 487.9 (95% CI 433.6–548.6; Java-Bali), 635.9 (95% CI 564.9–715.1; Sumatra), to 2,129.8 (95% CI 1,664.0–2,735.6; other islands). Based on chest x-ray, the TB prevalence varied from 152.1 (95% CI 147.9–156.3; Java-Bali), 159.2 (95% CI 154.1–164.3; Sumatra), to 864 (95% CI 809–921.4; other islands). Based on sputum genetic test, the TB prevalence ranged from 838.7 (95% CI 748.4–900.8; Java-Bali), 875 (95% CI 775.4–934.2; Sumatra), to 941.2 (95% CI 663.6–992.3; other islands).

Conclusions

The variation of TB prevalence across geographical regions could be confounded by the diagnostic approaches.

Trial registration

This study was approved by the Institutional Review Board of Chulalongkorn University (IRB No. 684/63).

Spatial analysis of risk areas for the development of tuberculosis and treatment outcomes

OBJECTIVES

to identify risk clusters for the occurrence of tuberculosis and its treatment outcomes.

METHODS

ecological study, in a city in Maranhão, using data from the Notifiable Diseases Information System. Point density analysis and isotonic scanning techniques were used to identify areas with the highest occurrence of treatment outcomes and identify risk areas for possible tuberculosis cases.

RESULTS

most tuberculosis cases occurred in the male, adult, brown-skinned population. Also, most of the reported cases were classified as pulmonary and as new cases that progressed to a cure. The areas with the highest density of cure, death and abandonment are located in the central region of the city.

CONCLUSIONS

the central region of the urban area of the city, with high demographic density and poor sanitary and socioeconomic conditions, presented a greater cluster of tuberculosis cases.

Epidemiological characteristics of tuberculosis and effects of meteorological factors and air pollutants on tuberculosis in Shijiazhuang, China: A distribution lag non-linear analysis

BACKGROUND

Tuberculosis (TB) is a serious public health problem in China. There is evidence to prove that meteorological factors and exposure to air pollutants have a certain impact on TB. But the evidence of this relationship is insufficient, and the conclusions are inconsistent.

METHODS

Descriptive epidemiological methods were used to describe the distribution characteristics of TB in Shijiazhuang in the past five years. Through the generalized linear regression model (GLM) and the generalized additive model (GAM), the risk factors that affect the incidence of TB are screened. A combination of GLM and distribution lag nonlinear model (DLNM) was used to evaluate the lag effect of environmental factors on the TB. Results were tested for robustness by sensitivity analysis.

RESULTS

The incidence of TB in Shijiazhuang showed a downward trend year by year, with seasonality and periodicity. Every 10 μg/m³ of PM₁₀ changes, the RR distribution is bimodal. The first peak of RR occurs on the second day of lag (RR = 1.00166, 95% CI: 1.00023, 1.00390); the second risk period starts from 13th day of lag and peaks on15th day (RR = 1.00209, 95% CI: 1.00076, 1.00341), both of which are statistically significant. The cumulative effect of increasing 10 μg/m³ showed a similar bimodal distribution. Time zones where the RR makes sense are days 4-6 and 13-20. RR peaked on the 18th day (RR = 1.02239, 95% CI: 1.00623, 1.03882). The RR has a linear relationship with the concentration. Under the same concentration, the RR peaks within 15-20 days.

CONCLUSION

TB in Shijiazhuang City showed a downward trend year by year, with obvious seasonal fluctuations. The air pollutant PM₁₀ increases the risk of TB. The development of TB has a short-term lag and cumulative lag effects. We should focus on protecting susceptible people from TB in spring and autumn, and strengthen the monitoring and emission management of PM₁₀ in the atmosphere.

Association of polymorphisms of innate immunity-related genes and tuberculosis susceptibility in Mongolian population

BACKGROUNDS

Genetic polymorphism of the toll-like receptor 2, 4 (TLR2, TLR4) and natural resistance-associated macrophage protein 1 (NRAMP1) genes may affect host immune response to Mycobacterium tuberculosis (Mtb) and lead to the variation of susceptibility to tuberculosis (TB) in humans. However, the association of single nucleotide polymorphisms (SNP) in these genes and the susceptibility to TB in Mongolian population has not been investigated.

METHODS

We conducted a genetic association study including 197 Mongolian TB patients and 217 Mongolian healthy controls in Inner Mongolia, China. DNA of blood samples was extracted and genotyped for 5 SNPs in TLR4, 4 SNPs in TLR2 and 5 SNPs in NRAMP1 by next-generation sequencing. A logistic regression was performed and odds ratios (OR) with 95% confidence intervals (CI) were calculated to estimate the risk at TB by each SNP.

RESULTS

The most significant locus associated with the susceptibility to TB was TLR4 rs11536889. The frequency for allele C of TLR4 rs11536889 was 16.0% in TB patients and 23.5% in healthy controls, respectively. Rs11536889 C/C genotype of TLR4 was significantly associated with the low susceptibility against TB compared to G/G genotype in the dominant model (OR 0.62, 95% CI 0.41-0.94).

CONCLUSIONS

The TLR4 rs11536889 polymorphisms might be an indicative of the low susceptibility to TB in Mongolian population, which provides valuable information for the generation of effective strategy or measurement against TB in Mongolian population.

Notifiable Respiratory Infectious Diseases in China: A Spatial-Temporal Epidemiology Analysis

Nowadays, tuberculosis, scarlet fever, measles, influenza, and mumps are five major notifiable respiratory infectious diseases (RIDs) in China. The objective of this study was to describe, visualize, and compare the spatial-temporal distributions of these five RIDs from 2006 to 2016. In addition to descriptive epidemiology analysis, seasonality and spatial autocorrelation analysis were also applied to explore the epidemiologic trends and spatial changing patterns of the five RIDs, respectively. The results indicated that the incidence of tuberculosis, measles, and mumps presented a downtrend trend, while those of scarlet fever and influenza was in a strong uptrend across the research period. The incidences of the five diseases all peaked in spring. There were significant spatial disparities in the distribution of tuberculosis, scarlet fever, and measles cases, with the hotspots mainly located in the western plateau region, northern plain region, and southern mountainous region. To conclude, notable epidemiological differences were observed across regions, indicating that some provincial units should pay more attention to prevent and control respiratory infectious diseases.

Spatio-temporal co-occurrence of hotspots of tuberculosis, poverty and air pollution in Lima, Peru

Growing evidence suggests pollution and other environmental factors have a role in the development of tuberculosis (TB), however, such studies have never been conducted in Peru. Considering the association between air pollution and specific geographic areas, our objective was to determine the spatial distribution and clustering of TB incident cases in Lima and their co-occurrence with clusters of fine particulate matter (PM2.5) and poverty. We found co-occurrences of clusters of elevated concentrations of air pollutants such as PM2.5, high poverty indexes, and high TB incidence in Lima. These findings suggest an interplay of socio-economic and environmental in driving TB incidence.

Spatial patterns of tuberculosis and HIV co-infection in Ethiopia

BACKGROUND

Tuberculosis (TB) and human immunodeficiency virus (HIV) are the leading causes of infectious-disease-related deaths in Ethiopia, but little is known about their spatial distribution across the country. The aim of this study was to investigate the spatial patterns of TB and HIV co-infection in Ethiopia at the district level.

METHODS

We conducted an ecological study using TB and HIV data reported from all regions of Ethiopia through the national Health Management Information System (HMIS), between June 2015 and June 2017. Spatial clustering was assessed using Moran's I statistic and Getis-Ord statistic. Spatial binomial regression models were constructed separately for the prevalence of TB among people living with HIV and for the prevalence of HIV among TB patients, with and without spatial components using a Bayesian approach.

RESULTS

A total of 1,830,880 HIV and 192,359 TB patients were included in the analysis. The prevalence of HIV among TB patients was 7.34%; hotspots were observed in districts located in Amhara, Afar, and Gambela regions, and cold spots were observed in Oromiya and Southern Nations, Nationalities, and People (SNNP) regions. The prevalence of TB among people living with HIV varied from 0.7% in Oromia region to 14.5% in Afar region. Hotspots of TB prevalence among people living with HIV were observed in districts located in Gambela, Afar, Somali, and Oromiya regions; whereas the cold spots were observed in districts located in Amhara and Tigray regions. The ecological-level factors associated with the prevalence of TB among people living with HIV were low wealth index (OR: 1.49; 95% CrI: 1.05, 2.05), low adult literacy rate (OR: 0.67; 95% CrI: 0.46, 0.94), and distance to an international border (OR: 0.61; 95% CrI: 0.40, 0.91). The factors associated with the prevalence of HIV among TB patients were poor health care access (OR: 0.76; 95% CrI: 0.59, 0.95), low wealth index (OR: 1.31; 95% CrI: 1.01, 1.67), and low adult literacy rate (OR: 1.37; 95% CrI: 1.03, 1.78).

CONCLUSION

Our study provides evidence for geographic clustering of TB/HIV co-infection in Ethiopia. Health care access, proximity to international borders, and demographic factors such as low wealth index and adult literacy were significantly associated with the prevalence of TB/HIV co-infection.