A study on the relationship between air pollution and pulmonary tuberculosis based on the general additive model in Wulumuqi, China

Modelling of tuberculosis dynamics incorporating indirect transmission of contaminated environment and infectivity of smear-negative individuals: A case study for Xinjiang, China

Xinjiang has been one of the high incidence areas of pulmonary tuberculosis (PTB) in China. Besides being infected by direct contacting with active PTB individuals (direct infection), the susceptible would be infected because of the exposure to the environment contaminated by Mycobacterium tuberculosis (indirect infection). Active PTB individuals include not only the smear-positive PTB (PTB+) but also the smear-negative PTB (PTB-) who are infectious due to their ability to release tiny Mycobacterium tuberculosis particles even in the absence of visible Mycobacterium tuberculosis in sputum. By taking account of direct/indirect infection and the difference between PTB+ and PTB- individuals in transmission capability, a periodic dynamical PTB transmission model is proposed. The model is fitted to the newly monthly PTB+ and PTB- cases in Xinjiang from 2008 to 2017 by Markov Chain Monte Carlo algorithm. Moreover, global sensitivity analysis is constructed to address the uncertainty of some key parameters by using Latin hypercube sampling and partial rank correlation coefficient methods. Basic reproduction number R0 for PTB transmission in Xinjiang is estimated to be 2.447 (95% CrI:(1.203, 3.844)), indicating that PTB has been prevalent in Xinjiang over the study period. Our results suggest that reducing the direct/indirect transmission rates, early screening, isolating and treating the latent, PTB+ and PTB- individuals, and enhancing the clearance of Mycobacterium tuberculosis in the environment could more effectively control PTB transmission in Xinjiang. The model fits the reported PTB data well and achieves acceptable prediction accuracy. We believe that our model can provide heuristic support for controlling PTB transmission in Xinjiang.

Exploring the impact of socioeconomic and natural factors on pulmonary tuberculosis incidence in China (2013-2019) using explainable machine learning: A nationwide study

Pulmonary tuberculosis (PTB) stands as a significant and prevalent infectious disease in China. Integrating 13 natural and socioeconomic factors, we conduct nine machine learning (ML) models alongside the Tree-Structured Parzen Estimator to predict the monthly PTB incidence rate from 2013 to 2019 in mainland China. With explainable ML techniques, our research highlights that population size, per capita GDP, and PM10 concentration emerge as the primary determinants influencing the PTB incidence rate. We delineate both the independent and interactive impacts of these factors on the PTB incidence rate. Furthermore, crucial thresholds associated with factors influencing the PTB incidence rate are identified. Taking factors that have a positive effect on reducing the incidence rate of PTB as an example, the thresholds at which the effects of factors PM2.5, PM10, O3, and RH on the incidence rate change from increase to decrease are 105.5 µg/m3, 75.5 µg/m3, 90.8 µg/m3, and 72.3 % respectively. Our work will contribute valuable insights for public health interventions.

Factors affecting the incidence of pulmonary tuberculosis based on the GTWR model in China, 2004-2021

Contra-posing panel data on the incidence of pulmonary tuberculosis (PTB) at the provincial level in China through the years of 2004-2021 and introducing a geographically and temporally weighted regression (GTWR) model were used to explore the effect of various factors on the incidence of PTB from the perspective of spatial heterogeneity. The principal component analysis (PCA) was used to extract the main information from twenty-two indexes under six macro-factors. The main influencing factors were determined by the Spearman correlation and multi-collinearity tests. After fitting different models, the GTWR model was used to analyse and obtain the distribution changes of regression coefficients. Six macro-factors and incidence of PTB were both correlated, and there was no collinearity between the variables. The fitting effect of the GTWR model was better than ordinary least-squares (OLS) and geographically weighted regression (GWR) models. The incidence of PTB in China was mainly affected by six macro-factors, namely medicine and health, transportation, environment, economy, disease, and educational quality. The influence degree showed an unbalanced trend in the spatial and temporal distribution.

Associations between air pollutants and acute exacerbation of drug-resistant tuberculosis: evidence from a prospective cohort study

BACKGROUND

Short-term exposure to air pollution may trigger symptoms of drug-resistant tuberculosis (DR-TB) through stimulating lung tissue, damaging tracheobronchial mucosa, the key anti-mycobacterium T cell immune function, and production and release of inflammatory cytokines.

OBJECTIVE

To investigate the association between acute exacerbations of DR-TB and short-term residential exposure to air pollutants (PM10, PM2.5, SO2, NO2, CO and O3) based on a large prospective cohort in Anhui Province, China.

METHOD

Patients were derived from a prospective cohort study of DR-TB in Anhui Province. All DR-TB patients underwent drug-susceptibility testing and prefecture-level reference laboratories confirmed their microbiologies. The case-crossover design was performed to evaluate the association between the risk of acute exacerbations of DR-TB and short-term residential exposure to air pollution.

RESULTS

Short-term NO2 exposure was significantly related to an elevated risk of first-time outpatient visit due to acute exacerbations of DR-TB(relative risk:1.159, 95% confidence interval:1.011 ~ 1.329). Stratification analyses revealed that the relationship between the risk of acute exacerbations and NO2 exposure was stronger in the elderly (age ≥ 65) DR-TB patients, and in individuals with a history of TB treatment.

CONCLUSIONS

NO2 Exposure was significantly associated with an elevated risk of acute exacerbation of DR-TB in Anhui Province, China.

Household air pollution and risk of pulmonary tuberculosis in HIV-Infected adults

BACKGROUND

In low- and middle-income countries countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection.

METHODS

We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB.

RESULTS

We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/week were more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm].

CONCLUSION

Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.

Association between ambient temperature, PM2.5 and tuberculosis in Northwest China

   Existing evidence suggested that the risk of tuberculosis (TB) infection was associated to the variations in temperature and PM2.5. A total of 9,111 cases of TB were reported in Ningxia Hui Autonomous Region, China from 2013 to 2015 on a daily basis, and 57.2% of them were male. The TB risk was more prominent for a lower temperature in males (RR of 1.724, 95% CI: 1.241, 2.394), the aged over 64 years (RR of 2.241, 95% CI: 1.554, 3.231), and the high mobility occupation subpopulation (RR of 2.758, 95% CI: 1.745, 4.359). High concentration of PM2.5 showed a short-term effect and was only associated with an increased risk in the early stages of exposure for the female, and aged 36-64 years group. There were 15.06% (1370 cases) of cases of TB may be attributable to the temperature, and 2.94% (268 cases) may be attributable to the increase of PM2.5 exposures. Low temperatures may be associated with significantly increase in the risk of TB, and high PM2.5 concentrations have a short-term association on increasing the risk of TB. Strengthening the monitoring and regular prevention and control of high risk groups will provide scientific guidance to reduce the incidence of TB.

Air pollutants in bronchoalveolar lavage fluid and pulmonary tuberculosis: A mediation analysis of gene-specific methylation

Particulate matter (PM) exposure could alter the risk of tuberculosis, but the underlying mechanism is still unclear. We enrolled 132 pulmonary tuberculosis (PTB) patients and 30 controls. Bronchoalveolar lavage fluid samples were collected from all participants to detect organochlorine pesticides, polycyclic aromatic hydrocarbons, metal elements, and DNA methylation of immunity-related genes. We observed that γ-HCH, Bap, Sr, Ag, and Sn were related to an increased risk of PTB, while Cu and Ba had a negative effect. IFN-γ, IL-17A, IL-2, and IL-23 had a higher level in the PTB group, while IL-4 was lower. The methylation of 18 CpG sites was statistically associated with PTB risk. The methylation at the IL-4_06_121 site showed a significant mediating role on γ-HCH, Sr, and Sn. Our study suggests that PM exposure can increase the risk of tuberculosis by affecting DNA methylation and cytokine expression.

Household Air Pollution and Risk of Pulmonary Tuberculosis in HIV-Infected Adults

Background

In developing countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection.

Methods

We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB.

Results

We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/weekwere more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm].

Conclusion

Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.

Short-term PM2.5 exposure induces transient lung injury and repair

Exposure to fine atmospheric particulate matter (PM) is known to induce lung inflammation and injury; however, the way in which sophisticated endogenous lung repair and regenerative programs respond to this exposure remains unknown. In this study, we established a whole-body mouse exposure model to mimic real scenarios. Exposure to fine PM (PM with an aerodynamic diameter ≤ 2.5 µm [PM2.5]; mean 1.05 mg/m3) for 1-month elicited inflammatory infiltration and epithelial alterations in the lung, which were resolved 6 months after cessation of exposure. Immune cells that responded to PM2.5 exposure mainly included macrophages and neutrophils. During PM2.5 exposure, alveolar epithelial type 2 cells initiated rapid repair of alveolar epithelial mucosa through proliferation. However, the reparative capacity of airway progenitor cells (club cells) was impaired, which may have been related to the oxidative production of neutrophils or macrophages, as suggested in organoid co-cultures. These data suggested that the pulmonary toxic effects of short-term exposure to fine atmospheric PM at a certain dosage could be overcome through tissue reparative mechanisms.

Association of air pollutants and meteorological factors with tuberculosis: a national multicenter ecological study in China

The impact of weather variability and air pollutants on tuberculosis (TB) has been a research hotspot. Previous studies have mostly been limited to a certain area or with a small sample size of cases, and multi-scale systematic studies are lacking. In this study, 14,816,329 TB cases were collected from 31 provinces in China between 2004 and 2018 to estimate the association between TB risk and meteorological factors and air pollutants using a two-stage time-series analysis. The impact and lagged time of meteorological factors and air pollutants on TB risk varied greatly in different provinces and regions. Overall cumulative exposure-response summary associations across 31 provinces suggested that high monthly mean relative humidity (RH) (66.8-82.4%, percentile56-100 (P56-100)), rainfall (316.5-331.1 mm, P96-100), PM2.5 exposure concentration (93.3-145.0 μg/m3, P58-100), and low monthly mean wind speed (1.6-2.1 m/s, P0-38) increased the risk of TB incidence, with a relative risk (RR) of 1.10 (95% CI: 1.04-1.16), 1.10 (95% CI: 1.03-1.16), 2.08 (95% CI: 1.18-3.65), and 2.06 (95% CI: 1.27-3.33), and attributable risk percent (AR%) of 9%, 9%, 52%, and 51%, respectively. Conversely, high monthly average wind speed (2.3-2.9 m/s, P54-100) and mean temperature (20.2-25.3 °C, P79-96), and low monthly average rainfall (2.4-25.2 mm, P0-7) and concentration of SO2 (8.1-21.2 μg/m3, P0-16) exposure decreased the risk of TB incidence, with an overall cumulative RR of 0.92 (95% CI: 0.87-0.98), 0.74 (95% CI: 0.59-0.94), 0.87 (95% CI: 0.79-0.95), and 0.72 (95% CI: 0.56-0.93), respectively. Our study provided insights into future planning of public health interventions for TB.

Influential factors of tuberculosis in mainland China based on MGWR model

Tuberculosis (TB), as a respiratory infectious disease, has damaged public health globally for decades, and mainland China has always been an area with high incidence of TB. Since the outbreak of COVID-19, it has seriously occupied medical resources and affected medical treatment of TB patients. Therefore, the authenticity and reliability of TB data during this period have also been questioned by many researchers. In response to this situation, this paper excludes the data from 2019 to the present, and collects the data of TB incidence in mainland China and the data of 11 influencing factors from 2014 to 2018. Using spatial autocorrelation methods and multiscale geographically weighted regression (MGWR) model to study the temporal and spatial distribution of TB incidence in mainland China and the influence of selected influencing factors on TB incidence. The experimental results show that the distribution of TB patients in mainland China shows spatial aggregation and spatial heterogeneity during this period. And the R2 and the adjusted R2 of MGWR model are 0.932 and 0.910, which are significantly better than OLS model (0.466, 0.429) and GWR model (0.836, 0.797). The fitting accuracy indicators MAE, MSE and MAPE of MGWR model reached 5.802075, 110.865107 and 0.088215 respectively, which also show that the overall fitting effect is significantly better than OLS model (19.987574, 869.181549, 0.314281) and GWR model (10.508819, 267.176741, 0.169292). Therefore, this model is based on real and reliable TB data, which provides decision-making references for the prevention and control of TB in mainland China and other countries.

Environment pollutants exposure affects the endogenous activation of within-host Mycobacterium tuberculosis

OBJECTIVE

Epidemiological studies have linked ambient pollutants with tuberculosis (TB) risk, but the association has not been fully understood. Here, for the first time, we applied whole-genome sequencing (WGS) to assess the reproductive state of Mycobacterium tuberculosis (MTB) by profiling the mutation rate of MTB (MTBMR) during within-host endogenous reactivated progression, intending to dissect the actual effects of ambient pollutants on the endogenous reactivation.

METHODS

We conducted a retrospective cohort study on bacteriologically confirmed TB patients and followed them for relapse in Jiangsu and Sichuan Province, China. Endogenous and exogenous activation were distinguished by WGS of the pathogen. The average concentration of air pollution was estimated by considering a lag of 0-1 to 0-12 months. We applied a generalized additive model with a Poisson function to evaluate the relationships between ambient pollutants exposure and MTBMR.

RESULTS

In the single-pollutant adjusted models, the maximum effect for PM₁₀ (MTBMR increase: 81.87%, 95% CI: 38.38, 139.03) and PM_2.5 (MTBMR increase: 73.91%, 95% CI: 22.17, 147.55) was observed at a lag of 0-12 months for every 10 μg/m³ increase. For SO₂, the maximum effect was observed at lag 0-8 months, with MTBMR increasing by 128.06% (95% CI: 45.92, 256.44); and for NO₂, the maximum effect was observed at lag 0-9 months, with MTBMR increasing by 124.02% (95% CI: 34.5, 273.14). In contrast, the O₃ concentration was inversely associated with MTBMR, and the maximum reduction of MTBMR was 6.18% (95% CI: -9.24, -3.02) at a lag of 0-9 months. Similar results were observed for multi-pollutant models.

CONCLUSIONS

Increased exposure to ambient pollutants (PM₁₀, PM_2.5, SO₂, and NO₂) contributed to a faster MTBMR, indicating that MTB exhibits increased reproductive activity, thus accelerating within-host endogenous reactivation. O₃ exposure could decrease the MTBMR, suggesting that MTB exerts low reproductive activity by inhibiting within-host endogenous activation.

Association between long-term exposure to ambient air pollutants and the risk of tuberculosis: A time-series study in Nantong, China

Background

Increasing evidence has shown that the risk of tuberculosis (TB) might be related to the exposure to air pollutants; however, the findings are inconsistent and studies on long-term air pollutant exposure and TB risk are scarce. This study aime to assess the relationship between monthly exposure to air pollution and TB risk in Nantong, China.

Methods

We collected the time series data on the number of TB cases, as well as environmental and socioeconomic covariates from January 2005 to December 2020. The impact of air pollutant exposure on TB risk was evaluated using the distributed lag nonlinear model (DLNM). Stratified analyses were conducted to examine the effect modifications of sex and age on the association between air pollutants and TB risk. Sensitivity analyses were applied to test the stability of the model.

Results

There were a total of 54,096 cases of TB in Nantong during the study period. In the single-pollutant model, for each 10 μg/m³ increase in concentration, the pooled relative risks (RRs) of TB reached the maximum to 1.10 (95% confidence interval (CI): 1.04-1.16, lag 10 months) for particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5), 1.05 (95% CI: 1.01-1.10, lag 9 months) for particulate matter with aerodynamic diameter less than 10 μm (PM₁₀), and 1.11 (95%CI: 1.04-1.19, lag 10 months) for nitrogen dioxide (NO₂). Ozone (O₃) did not show significant effect on TB risk. Effect modifications of sex and age on the association between air pollutants and TB risk were not observed. The multi-pollutant model results showed no significant variation compared with the single-pollutant model.

Conclusions

Our study suggests that air pollutants pose a substantial threat to the TB risk. Reducing air pollution might be crucial for TB prevention and control.

Short-term exposure to air pollution and outpatient visits for conjunctivitis: a time-series analysis in Urumqi, China

Conjunctivitis is an inflammatory disease of the conjunctival tissue caused by a variety of causes; despite the conjunctiva being directly exposed to the external atmospheric environment, the important role of air pollution is not fully evaluated, especially in areas with poor air quality undergoing rapid economic and industrial development. Information on 59,731 outpatient conjunctivitis visits from 1 January 2013 to 31 December 2020 was obtained from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China), and data on six air pollutants including particulate matter with a median aerometric diameter of less than 10 and 2.5 mm (PM₁₀ and PM_2.5, respectively), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) from eleven standard urban background fixed air quality monitors were also recorded. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effect of exposure to air pollutants on the risk of conjunctivitis outpatient visits. Further subgroup analyses were conducted for gender, age, and season, as well as the type of conjunctivitis. Single and multi-pollutant models showed that exposure to PM_2.5, PM₁₀, NO₂, CO, and O₃ was associated with increased risk of outpatient conjunctivitis visits on the lag 0 day and various other lag days. Variations in the effect estimates on direction and magnitude were found in different subgroup analyses. We conducted the first time-series analysis with the longest duration as well as the largest sample size in Northwest China, which provides evidence that outpatient conjunctivitis visits is significantly associated with air pollution in Urumqi, China. Meanwhile, our results demonstrate the effectiveness of SO₂ reduction in reducing the risk of outpatient conjunctivitis visits in the Urumqi region and reaffirm the need to implement special air pollution control measures.

Associations between air pollutants and hospital admissions for chronic obstructive pulmonary disease in Jinan: potential benefits from air quality improvements

Evidence between air pollution and chronic obstructive pulmonary disease (COPD) is inconsistent and limited in China. In this study, we aim to examine the associations between air pollutants and hospital admissions for COPD, hoping to provide practical advice for prevention and control of COPD. Hospital admissions for COPD were collected from a Grade-A tertiary hospital in Jinan from 2014 to 2020. A generalized additive model (GAM) was used to examine the associations between air pollutants and hospital admissions for COPD. Stratified analysis was also conducted for gender, age (20-74 and ≥75 years), and season (warm and cold). The avoidable number of COPD hospital admissions was calculated when air pollutants were controlled under national and WHO standards. Over the study period, a total of 4,012 hospital admissions for COPD were recorded. The daily hospital admissions of COPD increased by 2.36% (95%CI: 0.13-4.65%) and 2.39% (95%CI: 0.19-4.65%) for per 10 μg/m³ increase of NO₂ and SO₂ concentrations at lag2, respectively. There was no statistically significant difference in health effects caused by increased concentrations of PM_2.5, PM₁₀, CO, and O₃. The health effects of increased SO₂ concentration were stronger in women, the ≥75 years old people and the cold season. About 2 (95%CI: 0-3), 64 (95%CI: 4-132) and 86 (95%CI: 6-177) COPD admissions would be avoided when the SO₂ concentration was controlled below the NAAQS-II (150 μg/m³), NAAQS-I (50 μg/m³), and WHO's AQG2021 standard (40 μg/m³), respectively. These findings suggest that short-term exposure to NO₂ and SO₂ was associated with increased risks of daily COPD admissions, especially for females and the elderly. The control of SO₂ and NO₂ under the national and WHO standards could avoid more COPD admissions and obtain greater health benefits.

A comparative study of three models to analyze the impact of air pollutants on the number of pulmonary tuberculosis cases in Urumqi, Xinjiang

In this paper, we separately constructed ARIMA, ARIMAX, and RNN models to determine whether there exists an impact of the air pollutants (such as PM2.5, PM10, CO, O3, NO2, and SO2) on the number of pulmonary tuberculosis cases from January 2014 to December 2018 in Urumqi, Xinjiang. In addition, by using a new comprehensive evaluation index DISO to compare the performance of three models, it was demonstrated that ARIMAX (1,1,2) × (0,1,1)12 + PM2.5 (lag = 12) model was the optimal one, which was applied to predict the number of pulmonary tuberculosis cases in Urumqi from January 2019 to December 2019. The predicting results were in good agreement with the actual pulmonary tuberculosis cases and shown that pulmonary tuberculosis cases obviously declined, which indicated that the policies of environmental protection and universal health checkups in Urumqi have been very effective in recent years.

The association between air pollutants, meteorological factors and tuberculosis cases in Beijing, China: A seven-year time series study

BACKGROUND

Tuberculosis (TB) is a severe public health problem globally. Previous studies have revealed insufficient and inconsistent associations between air pollutants, meteorological factors and TB cases. Yet few studies have examined the associations between air pollutants, meteorological factors and TB cases in Beijing.

OBJECTIVE

The purpose of this study was to explore the impact of air pollutants and meteorological factors on TB in Beijing, and to provide novel insights into public health managers to formulate control strategies of TB.

METHODS

Data on the daily case of TB in Beijing during 2014-2020 were obtained from Chinese tuberculosis information management system. Concurrent data on the daily PM₁₀, PM_2.5, SO₂, NO₂, CO and O₃, were obtained from the online publication platform of the Chinese National Environmental Monitoring Center. Daily average temperature, average wind speed, relative humidity, sunshine duration and total precipitation were collected from the China Meteorological Science Data Sharing Service System. A distributed lag non-linear model was fitted to identify the non-linear exposure-response relationship and the lag effects between air pollutions, meteorological factors and TB cases in Beijing.

RESULTS

In the single-factor model, the excess risk (ER) of TB was significantly positively associated with every 10 μg/m³ increase in NO₂ in lag 1 week (ER: 1.3%; 95% confidence interval [CI]: 0.4%, 2.3%) and every 0.1 m/s increase in average wind speed in lag 5 weeks (ER: 0.3%; 95% CI: 0.1%, 0.5%), and was negatively associated with every 10 μg/m³ increase in O₃ in lag 1 week (ER: -1.2%; 95% CI: -1.8%, -0.5%), every 5 °C increase in average temperature (ER: -1.7%; 95% CI: -2.9%, -0.4%) and every 10% increase in average relative humidity (ER: -0.4%; 95% CI: -0.8%, -0.1%) in lag 10 weeks, respectively. In the multi-factor model, the lag effects between TB cases and air pollutants, meteorological factors were similar. The subgroup analysis suggests that the effects of NO₂, O₃, average wind speed and relative humidity on TB were greater in male or labor age subgroup, while the effect of CO was greater in the elderly. In addition, no significant associations were found between PM_2.5, SO_2, sunshine duration and TB cases.

CONCLUSION

Our findings provide a better understanding of air pollutants and meteorological factors driving tuberculosis occurrence in Beijing, which enhances the capacity of public health manager to target early warning and disease control policy-making.

Tuberculosis epidemiological trend in Sousse, Tunisia during twenty years (2000-2019)

Describe the epidemiology of tuberculosis in the last two decades (2000-2019) in the East region of Tunisia (city of Sousse). This was a descriptive retrospective analysis of notified incident cases of tuberculosis from 2000 to 2019 in Sousse Governorate, Tunisia. The data collection was done via the regional registry of tuberculosis. Stata software was used to characterize the socio-demographic and clinical profile of tuberculosis, to calculate its incidence, mortality and fatality rates and to determine predictive factors of mortality. R software was used to analyze the chronological trend of tuberculosis incidence and mortality. A total of 2606 incident cases of tuberculosis were declared from 2000 to 2019 in Sousse. The mean age was 39 ± 19 years with a sex ratio (male/female) of 1.19. Only one case was HIV positive among the total 2606 incident cases. Extra-pulmonary tuberculosis was the most recorded (1,534 cases, 58.9%). The mean annual case notification and deaths were 130 and four respectively. After adjusting for confounders, individuals with pulmonary tuberculosis were 1.9 significantly more likely to die from tuberculosis compared to those suffering from extra-pulmonary tuberculosis. There was a trend of increasing mortality with increasing age. The association was statistically significant only for those above 60 years' old who had 12.5 times higher odds of dying compared to those below 60 years. After adjusting for age and gender, with every year there was an increase in the total incidence rate (+0.35 per 100,000) with p = 0.005 and in the extra-pulmonary incidence (+0.27 per 100,000), with p = 0.001. This study demonstrated the increasing trend of tuberculosis in Sousse, Tunisia from 2000 to 2019. The national program against tuberculosis should enhance community knowledge and centralize the national and regional epidemiological information for better epidemiological surveillance.

Long-term exposure to ambient air pollution and greenness in relation to pulmonary tuberculosis in China: A nationwide modelling study

Previous studies have attempted to clarify the relationship between the occurrence of pulmonary tuberculosis (PTB) and exposure to air pollutants. However, evidence from multi-centres, particularly at the national level, is scarce, and no study has examined the modifying effect of greenness on air pollution-TB associations. In this study, we examined the association between long-term exposure to ambient air pollutants (PM₁₀ p.m._2.5, and O₃) and monthly PTB or smear-positive pulmonary tuberculosis (SPPTB) incidence to further evaluate whether these associations were affected by greenness in mainland China using a two-stage analytic procedure. PM_2.5 was positively associated with both PTB and SPPTB incidence, with relative risk (RR) of 1.12 (95% confidence interval [CI]: 1.03, 1.22) and 1.08 (95% CI: 1.02, 1.10) per 10 μg/m³ increase, respectively. Furthermore, PM₁₀ was positively associated with PTB incidence, with RR of 1.07 (95% CI: 1.01, 1.13). However, O₃ was not associated with the monthly incidence of PTB or SPPTB. The normalized difference vegetation index (NDVI) exhibited a modifying effect on the association between PM_2.5 exposure and SPPTB incidence in northern areas, with RR of 1.16 (95% CI: 1.03, 1.31) in lower mean annual NDVI areas than in the higher areas (RR = 0.98, 95% CI: 0.87, 1.09). This nationwide analysis indicated that NDVI could reduce the effect of air pollutants on TB incidence particularly in the northern areas. Long-term exposure to particulate matter (PM) may increase the occurrence of PTB or SPPTB in China, and further studies involving larger numbers of SPPTB cases are required to confirm the effects of PM exposure on SPPTB incidence in the future.

Epidemiological Characteristics and Spatial-Temporal Analysis of Tuberculosis at the County-Level in Shandong Province, China, 2016-2020

(1) Background: Tuberculosis (TB) is an infectious disease that seriously endangers health and restricts economic and social development. Shandong Province has the second largest population in China with a high TB burden. This study aimed to detect the epidemic characteristics and spatio-temporal pattern of reported TB incidence in Shandong Province and provide a scientific basis to develop more effective strategies for TB prevention and control. (2) Methods: The age, gender, and occupational distribution characteristics of the cases were described. The Seasonal-Trend LOESS decomposition method, global spatial autocorrelation statistic, local spatial autocorrelation statistics, and spatial-temporal scanning were used to decompose time series, analyze the spatial aggregation, detect cold and hot spots, and analyze the spatio-temporal aggregation of reported incidence. (3) Results: A total of 135,185 TB cases were reported in Shandong Province during the five years 2016-2020. Men and farmers are the main populations of TB patients. The time-series of reported tuberculosis incidence had a long-term decreasing trend with clear seasonality. There was aggregation in the spatial distribution, and the areas with a high reported incidence of TB were mainly clustered in the northwest and southeast of Shandong. The temporal scan also yielded similar results. (4) Conclusions: Health policy authorities should develop targeted prevention and control measures based on epidemiological characteristics to prevent and control TB more effectively.

A systematic review and meta-analysis on the association between ambient air pollution and pulmonary tuberculosis

There is inconclusive evidence on the association between ambient air pollution and pulmonary tuberculosis (PTB) incidence, tuberculosis-related hospital admission and mortality. This review aimed to assess the extent to which selected air pollutants are associated to PTB incidence, hospital admissions and mortality. This was a systematic review of studies published in English from January 1st, 1946, through May 31st, 2022, that quantitatively assessed the association between PM_2.5, PM₁₀, NO₂, SO₂, CO, O₃ and the incidence of, hospital admission or death from PTB. Medline, Embase, Scopus and The Cochrane Library were searched. Extracted data from eligible studies were analysed using STATA software. Random-effect meta-analysis was used to derive pooled adjusted risk and odds ratios. A total of 24 studies (10 time-series, 5 ecologic, 5 cohort, 2 case–control, 1 case cross-over, 1 cross-sectional) mainly from Asian countries were eligible and involved a total of 437,255 tuberculosis cases. For every 10 μg/m³ increment in air pollutant concentration, there was a significant association between exposure to PM_2.5 (pooled aRR = 1.12, 95% CI: 1.06–1.19, p < 0.001, N = 6); PM₁₀ (pooled aRR = 1.06, 95% CI: 1.01–1.12, p = 0.022, N = 8); SO₂ (pooled aRR = 1.08, 95% CI: 1.04–1.12, p < 0.001, N = 9); and the incidence of PTB. There was no association between exposure to CO (pooled aRR = 1.04, 95% CI: 0.98–1.11, p = 0.211, N = 4); NO₂ (pooled aRR = 1.08, 95% CI: 0.99–1.17, p = 0.057, N = 7); O₃ (pooled aRR = 1.00, 95% CI: 0.99–1.02, p = 0.910, N = 6) and the incidence of PTB. There was no association between the investigated air pollutants and mortality or hospital admissions due to PTB. Overall quality of evidence was graded as low (GRADE approach). Exposure to PM_2.5, PM₁₀ and SO₂ air pollutants was found to be associated with an increased incidence of PTB, while exposure to CO, NO₂ and O₃ was not. There was no observed association between exposure to these air pollutants and hospital admission or mortality due to PTB. The quality of the evidence generated, however, remains low. Addressing the tuberculosis epidemic by 2030 as per the 4th Sustainable Development Goal may require a more rigorous exploration of this association.

Spatio-temporal distribution of tuberculosis and the effects of environmental factors in China

Background

Although the World Health Organization reports that the incidence of tuberculosis in China is decreasing every year, the burden of tuberculosis in China is still very heavy. Understanding the spatial and temporal distribution pattern of tuberculosis in China and its influencing environmental factors will provide effective reference for the prevention and treatment of tuberculosis.

Methods

Data of TB incidence from 2010 to 2017 were collected. Time series and global spatial autocorrelation were used to analyze the temporal and spatial distribution pattern of tuberculosis incidence in China, Geodetector and Geographically Weighted Regression model were used to analyze the environmental factors affecting the TB incidence.

Results

In addition to 2007 and 2008, the TB incidence decreased in general. TB has a strong spatial aggregation. Cities in Northwest China have been showing a trend of high-value aggregation. In recent years, the center of gravity of high-value aggregation area in South China has moved further south. Temperature, humidity, precipitation, PM₁₀, PM_2.5, O₃, NO₂ and SO₂ have impacts on TB incidence, and in different regions, the environmental factors show regional differences.

Conclusions

Residents should pay more attention to the risk of developing TB caused by climate change and air pollutant exposure. Increased efforts should be placed on areas with high-value clustering in future public resource configurations.

Association of Daily Exposure to Air Pollutants with the Risk of Tuberculosis in Xuhui District of Shanghai, China

Previous studies have suggested that air pollutant exposure is related to tuberculosis (TB) risk, but results have not been consistent. This study evaluated the relation between daily air pollutant exposure and TB incidence in Shanghai from 2014 to 2019. Overall, there were four pollutants that were positively related to the risk of new TB cases. After a 5 μg/m³ increase, the maximum lag-specific and cumulative relative risk (RR) of SO₂ were 1.081, (95% CI: 1.035–1.129, lag: 3 days) and 1.616 (95% CI: 1.119–2.333, lag: 0–13 days), while for NO₂, they were 1.061 (95% CI: 1.015–1.11, lag: 4 days) and 1.8 (95% CI: 1.113–2.91, lag: 0–15 days). As for PM_2.5, with a 50 μg/m³ increase, the lag-specific and cumulative RR were 1.064 (95% CI: 1–1.132, lag: 6 days) and 3.101 (95% CI: 1.096–8.777, lag: 0–21 days), while for CO, the lag-specific RR was 1.03 (95% CI: 1.005–1.057, lag: 8 days) and the cumulative RR was 1.436 (95% CI: 1.004–2.053, lag: 0–16 days) with a 100 μg/m³ increase. The associations tended to be stronger in male and elderly patients and differed with seasons. Air pollutant exposure may be a risk factor for TB incidence.

Lagged Effects of Exposure to Air Pollutants on the Risk of Pulmonary Tuberculosis in a Highly Polluted Region

BACKGROUND

Although significant correlations have been observed between air pollutants and the development of pulmonary tuberculosis (PTB) in many developed countries, data are scarce for developing and highly polluted regions.

METHOD

A combined Poisson generalized linear regression-distributed lag nonlinear model was used to determine the associations between long-term exposure (2005-2017) to air pollutants and the risk of PTB in the Beijing-Tianjin-Hebei region.

RESULTS

The monthly PTB cases exhibited a fluctuating downward trend. For each 10 μg/m3 increase in concentration, the maximum lag-specific risk and cumulative relative risk (RR) were 1.011 (95% confidence interval (CI): 1.0091.012, lag: 3 months) and 1.042 (1.036-1.048, 5 months) for PM2.5, and 1.023 (1.015-1.031, 0 months) and 1.041 (1.026-1.055, 2 months) for NO2. The risk of PTB was negatively correlated with O3 exposure, and the minimum lag-specific risk and cumulative RR were 0.991 (95% CI: 0.987-0.994, lag: 0 months) and 0.974 (0.968-0.981, 4 months), respectively. No age-dependent effects were observed.

CONCLUSIONS

Our results revealed potential associations between outdoor exposure to PM2.5, NO2, and O3 and the risk of PTB. Further research should explore the corresponding interactions and potential mechanisms.

Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China

There is growing evidence that air pollution plays a role in TB, and most studies have been conducted in the core countries with inconsistent results. Few studies have comprehensively included the six common air pollutants, so they cannot consider whether various pollutants interact with each other. Our objectives were to investigate the association between short-term exposure to six common air pollutants and the risk of tuberculosis outpatient visits in Fuyang, China, 2015-2020. We combined the two models to explore the effects of exposure to six air pollutants on the risk of tuberculosis outpatient visits, including the Poisson generalized linear regression model and distributed lag non-linear model (DLNM). We performed stratified analyses for the season, type of cases, gender, and age. We used the lag-specific relative risks and cumulative relative risk obtained by increasing pollutant concentration by per 10 units to evaluate the connection between six air pollutants and TB; PM_2.5 (RR = 1.0018, 95% CI: 1.0004-1.0032, delay of 12 days) and SO₂ (RR = 1.0169, 95% CI: 1.0007-1.0333, lag 0-16 days) were 0.9549 (95% CI: 0.9389-0.9712, lag 0 day) and 0.8212 (95% CI: 0.7351-0.9173, 0-20-day lag). Stratified analyses showed that seasonal differences had a greater impact on TB, males were more likely to develop TB than females, older people were more likely to develop TB than younger people, and air pollution had a great impact on new cases. Exposure to O₃, CO, PM₁₀, PM_2.5, and NO₂ increases the risk of TB outpatient visits, except SO₂ which reduces the risk. The incidence of TB has seasonal fluctuations. It is necessary for the government to establish a sound environmental monitoring and early warning system to strengthen the monitoring and emission management of pollutants in the atmosphere. Management, prevention, and treatment measures should be developed for high-risk groups (males and older people), reducing the risk of TB by reducing their specific behaviors and changing their lifestyle. We need to pay more attention to the impact of seasonal effects on TB to protect TB patients and avoid a shortage of medical resources, and it is necessary for the government to develop some seasonal preventive measures in the future.

Study on the Associations between Meteorological Factors and the Incidence of Pulmonary Tuberculosis in Xinjiang, China

Pulmonary tuberculosis (PTB) has been a major threat to global public health. The association between meteorological factors and the incidence of PTB has been widely investigated by the generalized additive model, auto-regressive integrated moving average model and the distributed lag model, etc. However, these models could not address a non-linear or lag correlation between them. In this paper, a penalized distributed lag non-linear model, as a generalized and improved one, was applied to explore the influence of meteorological factors (such as air temperature, relative humidity and wind speed) on the PTB incidence in Xinjiang from 2004 to 2019. Moreover, we firstly use a comprehensive index (apparent temperature, AT) to access the impact of multiple meteorological factors on the incidence of PTB. It was found that the relationships between air temperature, relative humidity, wind speed, AT and PTB incidence were nonlinear (showed “wave-type “, “invested U-type”, “U-type” and “wave-type”, respectively). When air temperature at the lowest value (−16.1 °C) could increase the risk of PTB incidence with the highest relative risk (RR = 1.63, 95% CI: 1.21–2.20). An assessment of relative humidity demonstrated an increased risk of PTB incidence between 44.5% and 71.8% with the largest relative risk (RR = 1.49, 95% CI: 1.32–1.67) occurring at 59.2%. Both high and low wind speeds increased the risk of PTB incidence, especially at the lowest wind speed 1.4 m/s (RR = 2.20, 95% CI: 1.95–2.51). In particular, the lag effects of low and high AT on PTB incidence were nonlinear. The lag effects of extreme cold AT (−18.5 °C, 1st percentile) on PTB incidence reached a relative risk peak (RR = 2.18, 95% CI: 2.06–2.31) at lag 1 month. Overall, it was indicated that the environment with low air temperature, suitable relative humidity and wind speed is more conducive to the transmission of PTB, and low AT is associated significantly with increased risk of PTB in Xinjiang.

PM2.5 mediated alterations in the in vitro human granuloma and its effect on reactivation of mycobacteria

Exposure to particulate matter pollutant PM_2.5 diminishes the immune response to mycobacterial antigens relevant to contain the infection in the granuloma, thus leading to reactivation of latent bacilli. The present study was therefore designed based on the hypothesis that exposure to PM_2.5 affects the granuloma formation and reactivation of latent mycobacterial bacilli contained in the granuloma. For the sampling of PM_2.5, based on initial standardisations, Teflon filter was selected over the quartz filter. Two different approaches were used to study the effect of PM_2.5 on the human PBMC granuloma formed by Mycobacterium bovis BCG at multiplicity of infection (MOI) 0.1. In the first approach, granuloma formed in the presence of PM_2.5 was loosely packed and ill-defined with significant downregulation of dormancy-associated mycobacterial genes, upregulation of reactivation-associated rpfB gene along with a significant increase in TNFα level without any change in the bacterial load in terms of CFUs. In the second approach, preformed human PBMC granuloma using M. bovis BCG was treated with PM_2.5 that resulted in the disruption of granuloma architecture along with downregulation of not only dormancy-associated genes but also reactivation-associated rpfB gene of mycobacterial bacilli recovered from granuloma. However, there was no significant change in the host cytokine levels. Therefore, it can be inferred that PM_2.5 can modulate the granuloma formation in vitro as well as mycobacterial gene expression in the granuloma with a possible role in the reactivation of latent bacilli.

Associations between lung-deposited dose of particulate matter and culture-positive pulmonary tuberculosis pleurisy

Epidemiological studies identified the relationship between air pollution and pulmonary tuberculosis. Effects of lung-deposited dose of particulate matter (PM) on culture-positive pulmonary tuberculosis remain unclear. This study investigates the association between lung-deposited dose of PM and pulmonary tuberculosis pleurisy. A case-control study of subjects undergoing pleural effusion drainage of pulmonary tuberculosis (case) and chronic heart failure (control) was conducted. Metals and biomarkers were quantified in the pleural effusion. The air pollution exposure was measured and PM deposition in the head, tracheobronchial, alveolar region, and total lung region was estimated by Multiple-path Particle Dosimetry (MPPD) Model. We performed multiple logistic regression to examine the associations of these factors with the risk of tuberculosis. We observed that 1-μg/m³ increase in PM₁₀ was associated with 1.226-fold increased crude odds ratio (OR) of tuberculosis (95% confidence interval (CI): 1.023-1.469, p<0.05), 1-μg/m³ increase in PM_2.5-10 was associated with 1.482-fold increased crude OR of tuberculosis (95% CI: 1.048-2.097, p < 0.05), 1-ppb increase in NO₂ was associated with 1.218-fold increased crude OR of tuberculosis (95% CI: 1.025-1.447, p < 0.05), and 1-ppb increase in O₃ was associated with 0.735-fold decreased crude OR of tuberculosis (95% CI: 0.542 0.995). We observed 1-μg/m³ increase in PM deposition in head and nasal region was associated with 1.699-fold increased crude OR of tuberculosis (95% CI: 1.065-2.711, p < 0.05), 1-μg/m³ increase in PM deposition in tracheobronchial region was associated with 1.592-fold increased crude OR of tuberculosis (95% CI: 1.095-2.313, p < 0.05), 1-μg/m³ increase in PM deposition in alveolar region was associated with 3.981-fold increased crude OR of tuberculosis (95% CI: 1.280-12.386, p < 0.05), and 1-μg/m³ increase in PM deposition in total lung was associated with 1.511-fold increased crude OR of tuberculosis (95% CI: 1.050-2.173, p < 0.05). The results indicate that particle deposition in alveolar region could cause higher risk of pulmonary tuberculosis pleurisy than deposition in other lung regions.

Prediction of tuberculosis cases based on sociodemographic and environmental factors in gombak, Selangor, Malaysia: A comparative assessment of multiple linear regression and artificial neural network models

Background

Early prediction of tuberculosis (TB) cases is very crucial for its prevention and control. This study aims to predict the number of TB cases in Gombak based on sociodemographic and environmental factors.

Methods

The sociodemographic data of 3325 TB cases from January 2013 to December 2017 in Gombak district were collected from the MyTB web and TB Information System database. Environmental data were obtained from the Department of Environment, Malaysia; Department of Irrigation and Drainage, Malaysia; and Malaysian Metrological Department from July 2012 to December 2017. Multiple linear regression (MLR) and artificial neural network (ANN) were used to develop the prediction model of TB cases. The models that used sociodemographic variables as the input datasets were referred as MLR1 and ANN1, whereas environmental variables were represented as MLR2 and ANN2 and both sociodemographic and environmental variables together were indicated as MLR3 and ANN3.

Results

The ANN was found to be superior to MLR with higher adjusted coefficient of determination (R²) values in predicting TB cases; the ranges were from 0.35 to 0.47 compared to 0.07 to 0.14, respectively. The best TB prediction model, that is, ANN3 was derived from nationality, residency, income status, CO, NO₂, SO₂, PM₁₀, rainfall, temperature, and atmospheric pressure, with the highest adjusted R² value of 0.47, errors below 6, and accuracies above 96%.

Conclusions

It is envisaged that the application of the ANN algorithm based on both sociodemographic and environmental factors may enable a more accurate modeling for predicting TB cases.

Significance between air pollutants, meteorological factors, and COVID-19 infections: probable evidences in India

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman's correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2, and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 μg/m3 increase during (Lag0-14) in PM2.5, PM10, and NO2 resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

Association between ambient air pollution and tuberculosis risk: A systematic review and meta-analysis

There is a growing body of evidence suggesting an association between air pollution exposure and tuberculosis (TB) incidence, but no meta-analysis has assembled all evidence so far. This review and meta-analysis aimed to derive a more reliable estimation on the association between air pollution and TB incidence. PubMed, Embase and Web of Science electronic databases were systemically searched for eligible literature. The PECO framework was used to form the eligibility criteria. Effect estimates and 95% confidence intervals (CIs) published in the included studies were pooled quantitatively. Seventeen articles met the inclusion criteria. The pooled estimates showed that long-term exposure to particulate matter with an aerodynamic diameter ≤10 μm (PM₁₀) was associated with increased incidence of TB (per 10 μg/m³ increase in concentrations of PM₁₀: risk ratios (RR) = 1.058, 95% CI: 1.021-1.095). Besides, long-term exposure to sulfur dioxide (SO₂) and nitrogen dioxide (NO₂) were significantly associated with TB incidence (per 1 ppb increase, SO₂: RR = 1.016, 95% CI: 1.001-1.031; NO₂: 1.010, 95% CI: 1.002-1.017). We did not find a significant association of PM_2.5, ozone (O₃) or carbon monoxide (CO) with TB risk, regardless of long-term or short-term exposure. However, in view of the 2016 ASA Statement and the biological plausibility of PM_2.5 damaging host immunity, the association between PM_2.5 and TB risk remains to be further established. This meta-analysis shows that long-term exposure to PM₁₀, SO₂ or NO₂ is associated with increased odds of TB, and the specific biological mechanisms warrant further research.

Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia

Tuberculosis (TB) cases have increased drastically over the last two decades and it remains as one of the deadliest infectious diseases in Malaysia. This cross-sectional study aimed to establish the spatial distribution of TB cases and its association with the sociodemographic and environmental factors in the Gombak district. The sociodemographic data of 3325 TB cases such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from 1st January 2013 to 31st December 2017 in Gombak district were collected from the MyTB web and Tuberculosis Information System (TBIS) database at the Gombak District Health Office and Rawang Health Clinic. Environmental data consisting of air pollution such as air quality index (AQI), carbon monoxide (CO), nitrogen dioxide (NO₂), sulphur dioxide (SO₂), and particulate matter 10 (PM₁₀,) were obtained from the Department of Environment Malaysia from 1st July 2012 to 31st December 2017; whereas weather data such as rainfall were obtained from the Department of Irrigation and Drainage Malaysia and relative humidity, temperature, wind speed, and atmospheric pressure were obtained from the Malaysia Meteorological Department in the same period. Global Moran’s I, kernel density estimation, Getis-Ord Gi* statistics, and heat maps were applied to identify the spatial pattern of TB cases. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to determine the spatial association of sociodemographic and environmental factors with the TB cases. Spatial autocorrelation analysis indicated that the cases was clustered (p<0.05) over the five-year period and year 2016 and 2017 while random pattern (p>0.05) was observed from year 2013 to 2015. Kernel density estimation identified the high-density regions while Getis-Ord Gi* statistics observed hotspot locations, whereby consistently located in the southwestern part of the study area. This could be attributed to the overcrowding of inmates in the Sungai Buloh prison located there. Sociodemographic factors such as gender, nationality, employment status, health care worker status, income status, residency, and smoking status as well as; environmental factors such as AQI (lag 1), CO (lag 2), NO₂ (lag 2), SO₂ (lag 1), PM₁₀ (lag 5), rainfall (lag 2), relative humidity (lag 4), temperature (lag 2), wind speed (lag 4), and atmospheric pressure (lag 6) were associated with TB cases (p<0.05). The GWR model based on the environmental factors i.e. GWR2 was the best model to determine the spatial distribution of TB cases based on the highest R² value i.e. 0.98. The maps of estimated local coefficients in GWR models confirmed that the effects of sociodemographic and environmental factors on TB cases spatially varied. This study highlighted the importance of spatial analysis to identify areas with a high TB burden based on its associated factors, which further helps in improving targeted surveillance.

Logistic regression analysis of environmental and other variables and incidences of tuberculosis in respiratory patients

The objective of this study was to examine the association of 14 variables with TB in respiratory patients. The variables included: urban/rural, persons in 1200 sqft area, TB in family, crowding, smoking (family member), gender, age, education, smoking, workplace, kitchen location, cooking fuel, ventilation, and kerosene uses. Eight hundred respiratory patients were tested for sputum positive pulmonary TB; 500 had TB and 300 did not. An analysis of the unadjusted odds ratio (UOR) and adjusted OR (AOR) was undertaken using logistic regression to link the probability of TB incidences with the variables. There was an inconsistency in the significance of variables using UOR and AOR. A subset model of 4 variables (kerosene uses, ventilation, workplace, and gender) based on significant AOR was adjudged acceptable for estimating the probability of TB incidences. Uses of kerosene (AOR 2.62 (1.95, 3.54)) consistently related to incidences of TB. It was estimated that 50% reduction in kerosene uses could reduce the probability of TB by 13.29% in respiratory patients. The major recommendation was to replace kerosene uses from households with a supply of clean fuel like liquid petroleum or natural gas and rural electrification.