Seasonality of tuberculosis

The Impact of the Seasonal and Geographical Distribution of Tuberculosis in Sicily: A 6-Year Retrospective Study (2018-2023)

Background: Tuberculosis (TB) continues to be a major public health issue, with high mortality rates reported worldwide. It is worth noting that most of the hospitalizations for tuberculosis in the Sicilian region involve Italian-born individuals, underscoring the need to address this problem. Recent research on the geographic area and seasonality of infectious diseases, including tuberculosis, may aid in developing effective preventive measures. Objectives: This study aimed to evaluate the impact of the season and geographical area on tuberculosis disease prevalence in the Sicilian region. Methods: A retrospective study from January 2018 to May 2023 was conducted on patients with tuberculosis in the Sicilian region by analyzing computerized records on the Infectious Diseases Information System, currently named the Italian National Notification System (NSIS), of the Epidemiology Unit at Policlinico Paolo Giaccone University Hospital of Palermo and the Regional Reference Laboratory for Tuberculosis Surveillance and Control. Results: Eastern and Western Sicily were the geographical Sicilian areas with the highest frequency of patients with tuberculosis (52.2% and 42.6%, respectively). In comparison, Central Sicily had a significantly lower frequency of patients with tuberculosis (5.2%). Regarding the season, autumn was the season with the highest number of notification cases (28.9%), while spring was the season with the lowest frequency of patients with tuberculosis (19.7%). In autumn, we found significantly fewer patients with tuberculosis from Eastern Sicily (39.3%) and Central Sicily (1.5%), while Western Sicily had more patients with tuberculosis (59.3%). In spring, we found significantly more patients with tuberculosis from Eastern Sicily (64.1%), while Western and Central Sicily had significantly fewer patients with tuberculosis (23.9% and 12%, respectively). The presence of patients with tuberculosis did not significantly differ between geographical regions in summer and winter. Conclusions: Geographical area and seasonality significantly impact the distribution of tuberculosis cases in Sicily. These factors may be linked to different climatic conditions across the various geographical areas considered. Our findings suggest that climate can play a critical role in the spread of airborne infectious diseases, such as tuberculosis.

The effects of meteorological factors and air pollutants on the incidence of tuberculosis in people living with HIV/AIDS in subtropical Guangxi, China

BACKGROUND

Previous studies have shown the association between tuberculosis (TB) and meteorological factors/air pollutants. However, little information is available for people living with HIV/AIDS (PLWHA), who are highly susceptible to TB.

METHOD

Data regarding TB cases in PLWHA from 2014 to2020 were collected from the HIV antiviral therapy cohort in Guangxi, China. Meteorological and air pollutants data for the same period were obtained from the China Meteorological Science Data Sharing Service Network and Department of Ecology and Environment of Guangxi. A distribution lag non-linear model (DLNM) was used to evaluate the effects of meteorological factors and air pollutant exposure on the risk of TB in PLWHA.

RESULTS

A total of 2087 new or re-active TB cases were collected, which had a significant seasonal and periodic distribution. Compared with the median values, the maximum cumulative relative risk (RR) for TB in PLWHA was 0.663 (95% confidence interval [CI]: 0.507-0.866, lag 4 weeks) for a 5-unit increase in temperature, and 1.478 (95% CI: 1.116-1.957, lag 4 weeks) for a 2-unit increase in precipitation. However, neither wind speed nor PM10 had a significant cumulative lag effect. Extreme analysis demonstrated that the hot effect (RR = 0.638, 95%CI: 0.425-0.958, lag 4 weeks), the rainy effect (RR = 0.285, 95%CI: 0.135-0.599, lag 4 weeks), and the rainless effect (RR = 0.552, 95%CI: 0.322-0.947, lag 4 weeks) reduced the risk of TB. Furthermore, in the CD4(+) T cells < 200 cells/µL subgroup, temperature, precipitation, and PM10 had a significant hysteretic effect on TB incidence, while temperature and precipitation had a significant cumulative lag effect. However, these effects were not observed in the CD4(+) T cells ≥ 200 cells/µL subgroup.

CONCLUSION

For PLWHA in subtropical Guangxi, temperature and precipitation had a significant cumulative effect on TB incidence among PLWHA, while air pollutants had little effect. Moreover, the influence of meteorological factors on the incidence of TB also depends on the immune status of PLWHA.

The association between humidex and tuberculosis: a two-stage modelling nationwide study in China

BACKGROUND

Under a changing climate, the joint effects of temperature and relative humidity on tuberculosis (TB) are poorly understood. To address this research gap, we conducted a time-series study to explore the joint effects of temperature and relative humidity on TB incidence in China, considering potential modifiers.

METHODS

Weekly data on TB cases and meteorological factors in 22 cities across mainland China between 2011 and 2020 were collected. The proxy indicator for the combined exposure levels of temperature and relative humidity, Humidex, was calculated. First, a quasi-Poisson regression with the distributed lag non-linear model (DLNM) was constructed to examine the city-specific associations between humidex and TB incidence. Second, a multivariate meta-regression model was used to pool the city-specific effect estimates, and to explore the potential effect modifiers.

RESULTS

A total of 849,676 TB cases occurred in the 22 cities between 2011 and 2020. Overall, a conspicuous J-shaped relationship between humidex and TB incidence was discerned. Specifically, a decrease in humidex was positively correlated with an increased risk of TB incidence, with a maximum relative risk (RR) of 1.40 (95% CI: 1.11-1.76). The elevated RR of TB incidence associated with low humidex (5th humidex) appeared on week 3 and could persist until week 13, with a peak at approximately week 5 (RR: 1.03, 95% CI: 1.01-1.05). The effects of low humidex on TB incidence vary by Natural Growth Rate (NGR) levels.

CONCLUSION

A J-shaped exposure-response association existed between humidex and TB incidence in China. Humidex may act as a better predictor to forecast TB incidence compared to temperature and relative humidity alone, especially in regions with higher NGRs.

Holistic One Health Surveillance Framework: Synergizing Environmental, Animal, and Human Determinants for Enhanced Infectious Disease Management

Recent pandemics, including the COVID-19 outbreak, have brought up growing concerns about transmission of zoonotic diseases from animals to humans. This highlights the requirement for a novel approach to discern and address the escalating health threats. The One Health paradigm has been developed as a responsive strategy to confront forthcoming outbreaks through early warning, highlighting the interconnectedness of humans, animals, and their environment. The system employs several innovative methods such as the use of advanced technology, global collaboration, and data-driven decision-making to come up with an extraordinary solution for improving worldwide disease responses. This Review deliberates environmental, animal, and human factors that influence disease risk, analyzes the challenges and advantages inherent in using the One Health surveillance system, and demonstrates how these can be empowered by Big Data and Artificial Intelligence. The Holistic One Health Surveillance Framework presented herein holds the potential to revolutionize our capacity to monitor, understand, and mitigate the impact of infectious diseases on global populations.

The epidemiological situation of tuberculosis in Spain according to surveillance and hospitalization data, 2012-2020

BACKGROUND

Before the COVID-19 pandemic, tuberculosis (TB) was the leading cause of death from a single infectious agent. In Spain, TB notifications are registered through the National Epidemiological Surveillance Network (RENAVE). The Minimum Basic Data Set (CMBD) provides information on TB hospital discharges. This study aims to assess both registries to complete the picture of TB in order to improve national control strategies and make further progress toward its elimination.

METHODS

A retrospective study was performed considering CMBD´s hospital discharges with TB as first diagnosis and notifications to RENAVE between 2012 and 2020. After describing the records of both systems and their differences by using descriptive and multivariate analysis, annual incidences rates were calculated in order to evaluate temporal trends and geographical patters.

RESULTS

According to the CMBD database, there were 29,942 hospitalizations due to TB (65% pulmonary forms and 66% male) during the study period. RENAVE collected 44,520 reported cases, mostly males (62%) with pulmonary forms (72%). Young children were similar in both groups, showing the high frequency of hospitalization in this group. Almost all autonomous communities showed a downward trend, especially Asturias. Hospitalizations in 2020 were analyzed by month separately, and comparing with previous years, the impact of the COVID-19 pandemic can be seen.

CONCLUSIONS

A decreasing trend on TB incidence was observed in Spain since 2012, although this trend might change after COVID-19 pandemic. The analysis of both databases, CMBD and RENAVE, has contributed to improve our knowledge of TB in Spain and will help improve the control of this disease.

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.

The associations of ambient fine particles with tuberculosis incidence and the modification effects of ambient temperature: A nationwide time-series study in China

Ambient fine particulate matter (PM2.5) is a major air pollutant that poses significant risks to human health. However, little is known about the association of PM2.5 with tuberculosis (TB) incidence, and whether temperature modifies the association.This study aimed to explore the association between ambient PM2.5 exposure and TB incidence in China and the modification effects of temperature. Weekly meteorological data, PM2.5 concentrations, and TB incidence numbers were collected for 22 cities across Mainland China, from 2011 to 2020. A quasi-Poisson regression with the distributed lag non-linear model was used to assess city-specific PM2.5-TB associations. A multivariate meta-regression model was then used to pool the city-specific effect estimates, at the national and regional levels. A J-shaped PM2.5-TB relationship was observed at the national level for China. Compared to those with minimum PM2.5-TB risk, people who were exposed to the highest PM2.5 concentrations had a 26 % (RR:1.26, 95 % confidence interval [CI]: 1.05, 1.52) higher risk for TB incidence. J-shaped PM2.5-TB associations were also observed for most sub-groups, however, no significant modifying effects were found. While a trend was observed between low temperatures and increased exposure-response associations, these results were not significant. Overall, approximately 20 % of TB cases in the 22 study cities, over the period 2011-2020, could be attributed to PM2.5 exposure. Strengthening the monitoring and emission control of PM2.5 could aid the prevention and control of TB incidence.

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.

Impact of the COVID-19 pandemic on tuberculosis control in Indonesia: a nationwide longitudinal analysis of programme data

BACKGROUND

The impact of the COVID-19 pandemic on tuberculosis control in high-burden countries has not been adequately assessed. We aimed to estimate the impact of the COVID-19 pandemic on the national tuberculosis programme in Indonesia, in association with indicators of human development and health-system capacity across all 514 districts in 34 provinces.

METHODS

We did a nationwide longitudinal analysis to compare tuberculosis case notification, treatment coverage, and mortality rates in Indonesia before (2016-19) and during (2020-21) the COVID-19 pandemic. The following outcomes were assessed: the district-level quarterly reported tuberculosis case notification rate (number of all reported tuberculosis cases per 100 000 population), treatment coverage (proportion of tuberculosis patients who started treatment), and all-cause mortality rate in patients with tuberculosis (number of reported deaths per 100 000 population). District-level data on COVID-19 incidence and deaths, health-system capacity, and human development and sociodemographics were also analysed. Multilevel linear spline regression was done to assess quarterly time trends for the three outcomes.

FINDINGS

During the COVID-19 pandemic, the tuberculosis case notification rate declined by 26% (case notification rate ratio 0·74, 95% CI 0·72-0·77) and treatment coverage declined by 11% (treatment coverage ratio 0·89, 95% CI 0·88-0·90), but there was no significant increase in all-cause mortality (all-cause mortality rate ratio 0·97, 95% CI 0·91-1·04) compared with the pre-pandemic period. In the second year of the pandemic, we observed a partial recovery of the case notification rate from Q1 to Q4 of 2021, a persistent decrease in treatment coverage, and a decrease in the all-cause mortality rate from Q2 of 2020 to Q4 of 2021. The multivariable analysis showed that the reduction in the tuberculosis case notification rate was associated with a higher COVID-19 incidence rate (adjusted odds ratio 3·1, 95% CI 1·1-8·6, for the highest compared with the lowest group) and fewer GeneXpert machines for tuberculosis diagnosis (3·1, 1·0-9·4, for the lowest compared with the highest group) per 100 000 population. The reduction in tuberculosis treatment coverage was associated with higher COVID-19 incidence (adjusted odds ratio 11·7, 95% CI 1·5-93·4, for the highest compared with the lowest group), fewer primary health centres (10·6, 4·1-28·0, for the lowest compared with the middle-high group), and a very low number of doctors (0·3, 0·1-0·9, for the low-middle compared with the lowest group) per 100 000 population. No factors were shown to be significantly associated with all-cause mortality.

INTERPRETATION

The COVID-19 pandemic adversely and unevenly affected the national tuberculosis programme across Indonesia, with the greatest impacts observed in districts with the lowest health-system capacity. These disruptions could lead to an escalation in tuberculosis transmission in the coming years, warranting the need for intensified efforts to control tuberculosis and strengthen local health systems.

FUNDING

Wellcome Africa Asia Programme Vietnam.

TRANSLATION

For the Bahasa translation of the abstract see Supplementary Materials section.

Epidemiological trends and seasonal dynamics of tuberculosis in Southeastern Turkey

Background

Tuberculosis (TB) is an important public health issue. Determining TB trend and seasonal variability provides useful information for designing treatment strategies and control programs.

Aim

The present study attempts to investigate the epidemiological trend and the seasonal variations.

Materials and Methods

TB data containing 2450 cases were collected over a period of seven years in the province of Diyarbakir in southeast Turkey. Trend function and seasonal variability were investigated by statistical curve fitting, surface fitting, and autoregressive time series analysis.

Results

The study revealed a gradually decreasing trend in the number of TB cases over a period of seven years. Total TB incidence had seasonal variations (P = 0.04); there was a greater number of TB cases between April and July, with a peak in June. There were significant monthly seasonal variations with June peaks among females (P < 0.001), in patients in the age groups of 0-15 (P < 0.001) and 36-45 years (P < 0.001), in new cases (P < 0.001) and in the patients with pulmonary TB (P = 0.01). The extra-pulmonary TB cases peak in May (P = 0.01). Pulmonary TB and TB patients in the 36-45 age group had summer peak, while the other groups peaked at spring.

Conclusions

Spring and summer peaks detected in total TB cases and in many subgroups indicate that multicenter and comprehensive clinical studies are needed to explain these variations.

Short-term effect of ambient temperature and ambient temperature changes on the risk of warts outpatient visits in Hefei, China: a retrospective time-series study

Concerns are growing about the adverse health effects of ambient temperature and ambient temperature changes. However, the association between ambient temperature and ambient temperature changes on the risk of warts outpatient visits is poorly understood. Our study used the distributed lag non-linear model (DLNM) aimed to evaluate the association between ambient temperature, ambient temperature changes (including temperature change between neighboring days (TCN) and diurnal temperature range (DTR)), and warts outpatient visits. We also performed subgroup analyses in order to find susceptible populations by gender and age groups. The maximum relative risk (RR) of low ambient temperature (0 °C) for warts outpatient visits was 1.117 (95% CI: 1.041-1.198, lag 04 days), and the maximum RR of high ambient temperature (32 °C) for warts outpatient visits was 1.318 (95% CI: 1.083-1.605, lag 07 days). The large temperature drop (TCN =  - 3 °C) decreased the risk of warts visits, with the lowest RR value at the cumulative exposure of lag 7 days (RR = 0.888, 95% CI: 0.822-0.959), and the large temperature rise (TCN = 2 °C) increased the risk of warts visits, with the highest RR value at the cumulative exposure of lag 7 days (RR = 1.080, 95% CI: 1.022-1.142). Overall, both low and high ambient temperatures and large temperature rise can increase the risk of warts visits, while large temperature drop is a protective factor for warts visits. However, we did not find any association between DTR and warts visits. Furthermore, subgroup analyses showed that males and the young (0-17 years old) were more sensitive to low and high ambient temperatures, and the elderly (≥ 65 years old) were more susceptible to TCN. The results may provide valuable evidence for reducing the disease burden of warts in the future.

Native microbiomes in danger: Could One Health help to cope with this threat to global health?

Planetary health faces an emergency associated with global change. Climate change, the increase in world population and urban concentration, the hyperintensification of productive systems, and the associated changes in land use, among other factors, are generating a risky substrate for global health deterioration. The emergence of the coronavirus disease 2019 pandemic is an example of the problems that this situation can provoke. Several researchers and health professionals have addressed the role of microorganisms, particularly bacteria, in promoting global health, mainly in the past decades. However, global changes have contributed to the extinction of a wide array of bacterial species and the disruption of microbial communities that support the homeostasis of humans, animals, and the environment. The need to protect the diversity and richness of native microbiomes in biotic and abiotic environments is crucial but has been frequently underestimated. The "One Health" approach, based on integrating traditionally unconnected fields such as human, animal, and environmental health, could provide a helpful framework to face this challenge. Anyway, drastic political decisions will be needed to tackle this global health crisis, in which the preservation of native microbial resources plays a critical role, even in preventing the risk of a new pandemic. This review aims to explain the importance of native microbiomes in biotic and abiotic ecosystems and the need to consider bacterial extinction as a crucial problem that could be addressed under a One Health approach.

Epidemiological characteristics of pulmonary tuberculosis in patients with pneumoconiosis based on its social determinants and risk factors in China: a cross-sectional study from 27 provinces

BACKGROUND

Patients with pneumoconiosis have an elevated risk of contracting pulmonary tuberculosis (PTB) and need particular attention. However, extensive population-based studies on the prevalence of PTB in patients with pneumoconiosis have not been reported in China since 1992. This study aimed to investigate the epidemiological characteristics of PTB in patients with pneumoconiosis based on its social determinants and risk factors in China.

METHODS

Based on the Commission on Social Determinants of Health (CSDH) framework, data were obtained from a questionnaire survey of patients with pneumoconiosis from China's 27 provinces (autonomous regions, municipalities) from December 2017 to June 2021. By chi-square and multivariate logistic regression analyses, the epidemiological characteristics of PTB in the patients were identified based on its prevalence and odds ratio (OR) and associated social determinants and risk factors. The population attributable fractions (PAFs) of significant risk factors were also calculated.

RESULTS

The prevalence of PTB in patients with pneumoconiosis ( n  = 10,137) was 7.5% (95% confidence interval [CI]: 7.0-8.0%). Multivariate logistic regression analysis showed that risk factors included in-hospital exposure to patients with PTB (OR = 3.30, 95% CI: 2.77-3.93), clinically diagnosed cases (OR = 3.25, 95% CI: 2.42-4.34), and northeastern regions (OR = 2.41, 95% CI: 1.76-3.31). In addition, lack of work-related injury insurance (WRII), being born in a rural area, being unemployed, living in western regions, household exposure to patients with PTB, smoking, being underweight, complications of pulmonary bullae or pneumothorax, hospitalization history, and former drinkers among the rural patients were also statistically significant risk factors. Being born in a rural area, lack of WRII and in-hospital exposure to patients with PTB had higher PAFs, which were 13.2% (95% CI: 7.9-18.5%), 12.5% (95% CI: 8.3-16.7%), and 11.6% (95% CI: 8.8-14.3%), respectively.

CONCLUSION

The prevalence of PTB in pneumoconiosis remains high in China; it is basically in line with the CSDH models and has its characteristics.

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.

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.

Proportionate clinical burden of respiratory diseases in Indian outdoor services and its relationship with seasonal transitions and risk factors: The results of SWORD survey

Background

The Global Burden of Disease data suggest that respiratory diseases contribute to high morbidity in India. However, the factors responsible for high morbidity are not quite clear. Therefore, the Seasonal Waves Of Respiratory Disorders (SWORD) study was planned to estimate the point prevalence due to respiratory diseases in Indian OPD services and its association with risk factors and change in seasons.

Methods

In this point prevalence observational multicenter study conducted during 2017–18, participating physicians recorded information of consecutive patients in response to a questionnaire. The study was conducted on four predetermined days representing transition of Indian seasons i.e., February (winter), May (summer), August (monsoon), and November (autumn).

Results

The eligible number of patients from across 302 sites in India was 25,177. The mean age of study population was 46.1±18.1 years, 14102(56.0%) were males and 11075(44.0%) females. The common diagnoses were: asthma(29.8%), chronic obstructive pulmonary disease (COPD),15.6%, respiratory tract infections (RTIs),11.3%, and tuberculosis(8.7%). All these conditions showed significant seasonal trends (Asthma 31.4% autumn vs. 26.5% summer, COPD 21.1% winter vs. 8.1% summer, RTIs 13.3% winter vs. 4.3% summer, and tuberculosis 12.5% autumn vs. 4.1% summer, p<0.001 for each respectively). After adjustment for risk factors, asthma was significantly associated with exposure to molds (OR:1.12,CI:1.03–1.22), pet animals (OR:1.07,CI:1.01–1.14), recent-travel (OR:1.22,CI:1.13–1.32), and rain-wetting (OR:1.27,CI:1.15–1.40); and RTIs with rain-wetting (OR:1.53,CI:1.34–1.74), and recent-travel (OR:1.17,CI:1.05–1.30).

Conclusions

The SWORD study showed wide seasonal variations in outpatient attendance of patients with common respiratory conditions. Novel risk-factors associated with respiratory diseases were also identified.

Effects and Interaction of Meteorological Factors on Pulmonary Tuberculosis in Urumqi, China, 2013–2019

Background

Most existing studies have only investigated the delayed effect of meteorological factors on pulmonary tuberculosis (PTB). However, the effect of extreme climate and the interaction between meteorological factors on PTB has been rarely investigated.

Methods

Newly diagonsed PTB cases and meteorological factors in Urumqi in each week between 2013 and 2019 were collected. The lag-exposure-response relationship between meteorological factors and PTB was analyzed using the distributed lag non-linear model (DLNM). The generalized additive model (GAM) was used to visualize the interaction between meteorological factors. Stratified analysis was used to explore the impact of meteorological factors on PTB in different stratification and RERI, AP and SI were used to quantitatively evaluate the interaction between meteorological factors.

Results

A total of 16,793 newly diagnosed PTB cases were documented in Urumqi, China from 2013 to 2019. The median (interquartile range) temperature, relative humidity, wind speed, and PTB cases were measured as 11.3°C (−5.0–20.5), 57.7% (50.7–64.2), 4.1m/s (3.4–4.7), and 47 (37–56), respectively. The effects of temperature, relative humidity and wind speed on PTB were non-linear, which were found with the “N”-shaped, “L”-shaped, “N”-shaped distribution, respectively. With the median meteorological factor as a reference, extreme low temperature was found to have a protective effect on PTB. However, extreme high temperature, extreme high relative humidity, and extreme high wind speed were found to increase the risk of PTB and peaked at 31.8°C, 83.2%, and 7.6 m/s respectively. According to the existing monitoring data, no obvious interaction between meteorological factors was found, but low temperature and low humidity (RR = 1.149, 95%CI: 1.003–1.315), low temperature and low wind speed (RR = 1.273, 95%CI: 1.146–1.415) were more likely to cause the high incidence of PTB.

Conclusion

Temperature, relative humidity and wind speed were found to play vital roles in PTB incidence with delayed and non-linear effects. Extreme high temperature, extreme high relative humidity, and extreme high wind speed could increase the risk of PTB. Moreover, low temperature and low humidity, low temperature and low wind speed may increase the incidence of PTB.

Mycobacterium tuberculosis transmission in Birmingham, UK, 2009-19: An observational study

Background

Over 10-years of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in Birmingham presents an opportunity to explore epidemiological trends and risk factors for transmission in new detail.

Methods

Between 1st January 2009 and 15th June 2019, we obtained the first WGS isolate from every patient resident in a postcode district covered by Birmingham's centralised tuberculosis service. Data on patients' sex, country of birth, social risk-factors, anatomical locus of disease, and strain lineage were collected. Poisson harmonic regression was used to assess seasonal variation in case load and a mixed-effects multivariable Cox proportionate hazards model was used to assess risk factors for a future case arising in clusters defined by a 5 single nucleotide polymorphism (SNP) threshold, and by 12 SNPs in a sensitivity analysis.

Findings

511/1653 (31%) patients were genomically clustered with another. A seasonal variation in diagnoses was observed, peaking in spring, but only among clustered cases. Risk-factors for a future clustered case included UK-birth (aHR=2·03 (95%CI 1·35-3·04), p < 0·001), infectious (pulmonary/laryngeal/miliary) tuberculosis (aHR=3·08 (95%CI 1·98-4·78), p < 0·001), and M. tuberculosis lineage 3 (aHR=1·91 (95%CI 1·03-3·56), p = 0·041) and 4 (aHR=2·27 (95%CI 1·21-4·26), p = 0·011), vs. lineage 1. Similar results pertained to 12 SNP clusters, for which social risk-factors were also significant (aHR 1·72 (95%CI 1·02-2·93), p = 0·044). There was marked heterogeneity in transmission patterns between postcode districts.

Interpretation

There is seasonal variation in the diagnosis of genomically clustered, but not non-clustered, cases. Risk factors for clustering include UK-birth, infectious forms of tuberculosis, and infection with lineage 3 or 4.

Funding

Wellcome Trust, MRC, UKHSA.

Spatiotemporal Epidemiology of Tuberculosis in Thailand from 2011 to 2020

Tuberculosis is a leading cause of infectious disease globally, especially in developing countries. Better knowledge of spatial and temporal patterns of tuberculosis burden is important for effective control programs as well as informing resource and budget allocation. Studies have demonstrated that TB exhibits highly complex dynamics in both spatial and temporal dimensions at different levels. In Thailand, TB research has been primarily focused on surveys and clinical aspects of the disease burden with little attention on spatiotemporal heterogeneity. This study aimed to describe temporal trends and spatial patterns of TB incidence and mortality in Thailand from 2011 to 2020. Monthly TB case and death notification data were aggregated at the provincial level. Age-standardized incidence and mortality were calculated; time series and global and local clustering analyses were performed for the whole country. There was an overall decreasing trend with seasonal peaks in the winter. There was spatial heterogeneity with disease clusters in many regions, especially along international borders, suggesting that population movement and socioeconomic variables might affect the spatiotemporal distribution in Thailand. Understanding the space-time distribution of TB is useful for planning targeted disease control program activities. This is particularly important in low- and middle-income countries including Thailand to help prioritize allocation of limited resources.

Modeling and Predicting Pulmonary Tuberculosis Incidence and Its Association with Air Pollution and Meteorological Factors Using an ARIMAX Model: An Ecological Study in Ningbo of China

The autoregressive integrated moving average with exogenous regressors (ARIMAX) modeling studies of pulmonary tuberculosis (PTB) are still rare. This study aims to explore whether incorporating air pollution and meteorological factors can improve the performance of a time series model in predicting PTB. We collected the monthly incidence of PTB, records of six air pollutants and six meteorological factors in Ningbo of China from January 2015 to December 2019. Then, we constructed the ARIMA, univariate ARIMAX, and multivariate ARIMAX models. The ARIMAX model incorporated ambient factors, while the ARIMA model did not. After prewhitening, the cross-correlation analysis showed that PTB incidence was related to air pollution and meteorological factors with a lag effect. Air pollution and meteorological factors also had a correlation. We found that the multivariate ARIMAX model incorporating both the ozone with 0-month lag and the atmospheric pressure with 11-month lag had the best performance for predicting the incidence of PTB in 2019, with the lowest fitted mean absolute percentage error (MAPE) of 2.9097% and test MAPE of 9.2643%. However, ARIMAX has limited improvement in prediction accuracy compared with the ARIMA model. Our study also suggests the role of protecting the environment and reducing pollutants in controlling PTB and other infectious diseases.

Temporal trend of tuberculosis incidence and its spatial distribution in Macapá - Amapá

OBJECTIVE

To evaluate the temporal trend of tuberculosis incidence after the implementation of the rapid molecular test (RMT-TB), to identify whether tuberculosis presents seasonal variation and to classify the territory according to case density and risk areas in Macapá, Amapá.

METHODS

Ecological study of tuberculosis cases registered in the Sistema de Informação de Agravos de Notificação (SINAN - Information System for Notifiable Diseases) between 2001 and 2017. We used the Prais-Winsten test to classify the temporal trend of incidence and the interrupted time series to identify changes in the temporal trend before and after the implementation of the rapid molecular test, and to verify seasonality in the municipality. The Kernel estimator was used to classify case density and scan statistics to identify areas of tuberculosis risk.

RESULTS

A total of 1,730 cases were identified, with a decreasing temporal trend of tuberculosis incidence (-0.27% per month, 95%CI -0.13 to -0.41). The time series showed no change in level after the implementation of the GeneXpert®MTB/RIF molecular test; however, the incidence increased in the post-test period (+2.09% per month, 95%CI 0.92 to 3.27). Regarding the seasonal variation, it showed growth (+13.7%/month, 95%CI 4.71 to 23.87) from December to June, the rainy season - called amazon winter season -, and decrease (-9.21% per month, CI95% -1.37 to -16.63) in the other periods. We classified areas with high density of cases in the Central and Northern districts using Kernel and identified three protection clusters, SC1 (RR = 0.07), SC2 (RR = 0.23) and SC3 (RR = 0.36), and a high-risk cluster, SC4 (RR = 1.47), with the scan statistics.

CONCLUSION

The temporal trend of tuberculosis incidence was decreasing in the time series; however, detection increased after the introduction of RMT-TB, and tuberculosis showed seasonal behavior. The case distribution was heterogeneous, with a tendency to concentrate in vulnerable and risk territories, evidencing a pattern of disease inequality in the territory.

Bifurcation analysis of a model of tuberculosis epidemic with treatment of wider population suggesting a possible role in the seasonality of this disease

In this paper, a novel epidemiological model describing the evolution of tuberculosis in a human population is proposed. This model is of the form SEIR, where S stands for Susceptible people, E for Exposed (infected but not yet infectious) people, I for Infectious people, and R for Recovered people. The main characteristic of this model inspired from the disease biology and some realistic hypothesis is that the treatment is administered not only to infectious but also to exposed people. Moreover, this model is characterized by an open structure, as it considers the transfer of infected or infectious people to other regions more conducive to their care and accepts treatment for exposed or infectious patients coming from other regions without care facilities. Stability and bifurcation of the solutions of this model are investigated. It is found that saddle-focus bifurcation occurs when the contact parameter β passes through some critical values. The model undergoes a Hopf bifurcation when the quality of treatment r is considered as a bifurcation parameter. It is shown also that the system exhibits saddle-node bifurcation, which is a transcritical bifurcation between equilibrium points. Numerical simulations are done to illustrate these theoretical results. Amazingly, the Hopf bifurcation suggests an unexpected and never suggested explanation of seasonality of such a disease, linked to the quality of treatment.

Estimating the Effects of the COVID-19 Outbreak on the Reductions in Tuberculosis Cases and the Epidemiological Trends in China: A Causal Impact Analysis

Objective

COVID-19 may have a demonstrable influence on disease patterns. However, it remained unknown how tuberculosis (TB) epidemics are impacted by the COVID-19 outbreak. The purposes of this study are to evaluate the impacts of the COVID-19 outbreak on the decreases in the TB case notifications and to forecast the epidemiological trends in China.

Methods

The monthly TB incidents from January 2005 to December 2020 were taken. Then, we investigated the causal impacts of the COVID-19 pandemic on the TB case reductions using intervention analysis under the Bayesian structural time series (BSTS) method. Next, we split the observed values into different training and testing horizons to validate the forecasting performance of the BSTS method.

Results

The TB incidence was falling during 2005–2020, with an average annual percentage change of −3.186 (95% confidence interval [CI] −4.083 to −2.281), and showed a peak in March–April and a trough in January–February per year. The BSTS method assessed a monthly average reduction of 14% (95% CI 3.8% to 24%) in the TB case notifications from January–December 2020 owing to COVID-19 (probability of causal effect=99.684%, P=0.003), and this method generated a highly accurate forecast for all the testing horizons considering the small forecasting error rates and estimated a continued downward trend from 2021 to 2035 (annual percentage change =−2.869, 95% CI −3.056 to −2.681).

Conclusion

COVID-19 can cause medium- and longer-term consequences for the TB epidemics and the BSTS model has the potential to forecast the epidemiological trends of the TB incidence, which can be recommended as an automated application for public health policymaking in China. Considering the slow downward trend in the TB incidence, additional measures are required to accelerate the progress of the End TB Strategy.

Meteorological factors contribute to the risk of pulmonary tuberculosis: A multicenter study in eastern China

BACKGROUND

Most studies on associations between meteorological factors and tuberculosis (TB) were conducted in a single city, used different lag times, or merely explored the qualitative associations between meteorological factors and TB. Thus, we performed a multicenter study to quantitatively evaluate the effects of meteorological factors on the risk of pulmonary tuberculosis (PTB).

METHODS

We collected data on newly diagnosed PTB cases in 13 study sites in Jiangsu Province between January 1, 2014, and December 31, 2019. Data on meteorological factors, air pollutants, and socioeconomic factors at these sites during the same period were also collected. We applied the generalized additive mixed model to estimate the associations between meteorological factors and PTB.

RESULTS

There were 20,472 newly diagnosed PTB cases reported in the 13 study sites between 2014 and 2019. The median (interquartile range) weekly average temperature, weekly average wind speed, and weekly average relative humidity of these sites were 17.3 °C (8.0-24.1), 2.2 m/s (1.8-2.7), and 75.1% (67.1-82.0), respectively. In the single-meteorological-factor models, for a unit increase in weekly average temperature, weekly average wind speed, and weekly average relative humidity, the risk of PTB decreased by 0.9% [lag 0-13 weeks, 95% confidence interval (CI): -1.5, -0.4], increased by 56.2% (lag 0-16 weeks, 95% CI: 32.6, 84.0) when average wind speed was <3 m/s, and decreased by 28.1% (lag 0-14 weeks, 95% CI: -39.2, -14.9) when average relative humidity was ≥72%, respectively. Moreover, the associations remained significant in the multi-meteorological-factor models.

CONCLUSIONS

Average temperature and average relative humidity (≥72%) are negatively associated with the risk of PTB. In contrast, average wind speed (<3 m/s) is positively related to the risk of PTB, suggesting that an environment with low temperature, relatively high wind speed, and low relative humidity is conducive to the transmission of PTB.

Seasonality of tuberculosis in intermediate endemicity setting dominated by reactivation diseases in Hong Kong

Summer-spring predominance of tuberculosis (TB) has been widely reported. The relative contributions of exogenous recent infection versus endogenous reactivation to such seasonality remains poorly understood. Monthly TB notifications data between 2005 and 2017 in Hong Kong involving 64,386 cases (41% aged ≥ 65; male-to-female ratio 1.74:1) were examined for the timing, amplitude, and predictability of variation of seasonality. The observed seasonal variabilities were correlated with demographics and clinical presentations, using wavelet analysis coupled with dynamic generalised linear regression models. Overall, TB notifications peaked annually in June and July. No significant annual seasonality was demonstrated for children aged ≤ 14 irrespective of gender. The strongest seasonality was detected in the elderly (≥ 65) among males, while seasonal pattern was more prominent in the middle-aged (45–64) and adults (30–44) among females. The stronger TB seasonality among older adults in Hong Kong suggested that the pattern has been contributed largely by reactivation diseases precipitated by defective immunity whereas seasonal variation of recent infection was uncommon.

A scoping review on climate change and tuberculosis

Climate change is a global public health challenge. The changes in climatic factors affect the pattern and burden of tuberculosis, which is a worldwide public health problem affecting low and middle-income countries. However, the evidence related to the impact of climate change on tuberculosis is few and far between. This study is a scoping review following a five-stage version of Arksey and O'Malley's method. We searched the literature using the keywords and their combination in Google scholar, and PubMed. Climate change affects tuberculosis through diverse pathways: changes in climatic factors like temperature, humidity, and precipitation influence host response through alterations in vitamin D distribution, ultraviolet radiation, malnutrition, and other risk factors. The rise in extreme climatic events induces population displacement resulting in a greater number of vulnerable and risk populations of tuberculosis. It creates a conducive environment of tuberculosis transmission and development of active tuberculosis and disrupts tuberculosis diagnosis and treatment services. Therefore, it stands to reasons that climate change affects tuberculosis, particularly in highly vulnerable countries and areas. However, further studies and novel methodologies are required to address such a complex relationship and better understand the occurrence of tuberculosis attributable to climate change.

Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease

Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state >4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (TH17) cell-like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state-uniquely identifiable with multimodal analysis-from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.

Forecasting the Tuberculosis Incidence Using a Novel Ensemble Empirical Mode Decomposition-Based Data-Driven Hybrid Model in Tibet, China

Objective

The purpose of this study is to develop a novel data-driven hybrid model by fusing ensemble empirical mode decomposition (EEMD), seasonal autoregressive integrated moving average (SARIMA), with nonlinear autoregressive artificial neural network (NARNN), called EEMD-ARIMA-NARNN model, to assess and forecast the epidemic patterns of TB in Tibet.

Methods

The TB incidence from January 2006 to December 2017 was obtained, and then the time series was partitioned into training subsamples (from January 2006 to December 2016) and testing subsamples (from January to December 2017). Among them, the training set was used to develop the EEMD-SARIMA-NARNN combined model, whereas the testing set was used to validate the forecasting performance of the model. Whilst the forecasting accuracy level of this novel method was compared with the basic SARIMA model, basic NARNN model, error-trend-seasonal (ETS) model, and traditional SARIMA-NARNN mixture model.

Results

By comparing the accuracy level of the forecasting measurements including root-mean-square error, mean absolute deviation, mean error rate, mean absolute percentage error, and root-mean-square percentage error, it was shown that the EEMD-SARIMA-NARNN combined method produced lower error rates than the others. The descriptive statistics suggested that TB was a seasonal disease, peaking in late winter and early spring and a trough in autumn and early winter, and the TB epidemic indicated a drastic increase by a factor of 1.7 from 2006 to 2017 in Tibet, with average annual percentage change of 5.8 (95% confidence intervals: 3.5–8.1).

Conclusion

This novel data-driven hybrid method can better consider both linear and nonlinear components in the TB incidence than the others used in this study, which is of great help to estimate and forecast the future epidemic trends of TB in Tibet. Besides, under present trends, strict precautionary measures are required to reduce the spread of TB in Tibet.

Seasonal influence of tuberculosis diagnosis in Rwanda

Background

Tuberculosis (TB) remains a major global health concern. Previous research reveals that TB may have a seasonal peak during the spring and summer seasons in temperate climates; however, few studies have been conducted in tropical climates. This study evaluates the influence of seasonality on laboratory-confirmed TB diagnosis in Rwanda, a tropical country with two rainy and two dry seasons.

Methods

A retrospective chart review was performed at the University Teaching Hospital-Kigali (CHUK). From January 2016 to December 2017, 2717 CHUK patients with TB laboratory data were included. Data abstracted included patient demographics, season, HIV status, and TB laboratory results (microscopy, GeneXpert, culture). Univariate and multivariable logistic regression (adjusted for age, gender, and HIV status) analyses were performed to assess the association between season and laboratory-confirmed TB diagnoses.

Results

Patients presenting during rainy season periods had a lower odds of laboratory-confirmed TB diagnosis compared to the dry season (aOR=0.78, 95% CI 0.63–0.97, p=0.026) when controlling for age group, gender, and HIV status. Males, adults, and people living with HIV were more likely to have laboratory-confirmed TB diagnosis. On average, more people were tested for TB during the rainy season per month compared to the dry season (120.3 vs. 103.3), although this difference was not statistically significant.

Conclusion

In Rwanda, laboratory-confirmed TB case detection shows a seasonal variation with patients having higher odds of TB diagnosis occurring in the dry season. Further research is required to further elucidate this relationship and to delineate the mechanism of season influence on TB diagnosis.

The relationship between seasonality, latitude and tuberculosis notifications in Pakistan

Background

Pakistan ranks amongst the top 20 highest burden tuberculosis (TB) countries in the world. Approximately 369,548 cases of TB (all forms) were notified in 2018, with an estimated incidence of 265 per 100,000 people per year. In other settings, TB has been shown to demonstrate seasonal variation, with higher incidence in the spring/summer months and lower incidence in the autumn/winter; the amplitude of seasonal variation has also been reported to be higher with increasing distance from the equator.

Methods

Notifications of newly-diagnosed pulmonary and extrapulmonary TB cases were obtained for 139 districts in Pakistan from 2011 to 2017. Data were provided by the Pakistan National TB Control Programme, Islamabad, Pakistan. Statistical analyses were performed to determine whether there was seasonal variation in TB notifications in Pakistan; whether the amplitude of seasonal variation in TB notifications varied according to latitude; whether the amplitude of seasonal variation of TB in Pakistan differed between extrapulmonary TB vs. pulmonary TB. To assess the quarterly seasonality of TB, we used the X-13-ARIMA-SEATS seasonal adjustment programme from the United States Census Bureau. The mean difference and corresponding 95% confidence intervals of seasonal amplitudes between different latitudes and clinical phenotype of TB were estimated using linear regression.

Results

TB notifications were highest in quarter 2, and lowest in quarter 4. The mean amplitude of seasonal variation was 25.5% (95% CI 25.0 to 25.9%). The mean seasonal amplitude of TB notifications from latitude 24.5°N- < 26.5°N was 29.5% (95% CI 29.3 to 29.7%) whilst the mean seasonal amplitude of TB notifications from latitude 34.5°N - < 36.5°N was 21.7% (95% CI 19.6 to 23.9%). The mean seasonal amplitude of TB notifications across Pakistan between latitudes 24.5°N to 36.5°N reached statistically significant difference (p < 0.001). The amplitude of seasonal variation was greater for extrapulmonary TB (mean seasonal amplitude: 32.6, 95% CI 21.4 to 21.8%) vs. smear positive pulmonary TB mean seasonal amplitude: 21.6, 95% CI 32.1 to 33.1%), p < 0.001.

Conclusion

TB notifications in Pakistan exhibit seasonal variation with a peak in quarter 2 (April–June) and trough in quarter 4 (October–December). The amplitude of seasonality decreases with increasing latitude, and is more pronounced for extrapulmonary than for pulmonary TB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05899-x.

Association between household solid fuel use and tuberculosis: cross-sectional data from the Mongolian National Tuberculosis Prevalence Survey

BACKGROUND

Tuberculosis (TB) and indoor air pollution (IAP) are equally critical public health issues in the developing world. Mongolia is experiencing the double burden of TB and IAP due to solid fuel combustion. However, no study has assessed the relationship between household solid fuel use and TB in Mongolia. The present study aimed to assess the association between household solid fuel use and TB based on data from the Mongolian National Tuberculosis Prevalence Survey (MNTP Survey).

METHOD

The MNTP Survey was a nationally representative population-based cross-sectional survey targeting households in Mongolia from 2014 to 2015, with the aim of evaluating the prevalence of TB. The survey adopted a multistage cluster sampling design in accordance with the World Health Organization prevalence survey guidelines. Clusters with at least 500 residents were selected by random sampling. A sample size of 98 clusters with 54,100 participants was estimated to be required for the survey, and 41,450 participants were included in the final analysis of the present study. A structured questionnaire was used to collect information on environmental and individual factors related to TB. Physical examination, chest X-ray, and sputum examinations were also performed to diagnose TB.

RESULTS

The use of solid fuels for heating (adjusted odds ratio (aOR): 1.5; 95% confidence interval (CI): 1.1-2.1), male gender (aOR: 2.2; 95% CI: 1.6-3.2), divorced or widowed (aOR: 2.6; 95% CI: 1.7-3.8), daily smoker (aOR: 1.8; 95% CI: 1.3-2.5), contact with an active TB case (aOR: 1.7; 95% CI: 1.2-2.3), being underweight (aOR: 3.7; 95% CI: 2.4-5.7), and previous history of TB (aOR: 4.3; 95% CI: 3.0-6.1) were significantly associated with bacteriologically confirmed TB after adjusting for confounding variables.

CONCLUSION

The use of solid fuels for heating was significantly associated with active TB in Mongolian adults. Increased public awareness is needed on the use of household solid fuels, a source of IAP.

Temperature and humidity associated with increases in tuberculosis notifications: a time-series study in Hong Kong

Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13–15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02–1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0–63.6% at lagged 9–11 months expanded to 68.0–71.0% at lagged 12–17 months, reaching the highest risk of 1.06 (95% CI 1.01–1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.

Modeling the Impact of Seasonal Weather Variations on the Infectiology of Brucellosis

A deterministic mathematical model for brucellosis that incorporates seasonality on direct and indirect transmission parameters for domestic ruminants, wild animals, humans, and the environment was formulated and analyzed in this paper. Both analytical and numerical simulations are presented. From this study, the findings show that variations in seasonal weather have the great impact on the transmission dynamics of brucellosis in humans, livestock, and wild animals. Thus, in order for the disease to be controlled or eliminated, measures should be timely implemented upon the fluctuation in the transmission of the disease.

Short-term effect of ambient temperature change on the risk of tuberculosis admissions: Assessments of two exposure metrics

BACKGROUND

Although the effects of seasonal variations and ambient temperature on the incidence of tuberculosis (TB) have been well documented, it is still unknown whether ambient temperature change is an independent risk factor for TB. The aim of this study was to assess the association between ambient temperature change and the risk of TB admissions.

METHOD

A distributed lag non-linear model (DLNM) combined with Poisson generalized linear regression model was performed to assess the association between ambient temperature change and the risk of TB admissions from 2014 to 2018 in Hefei, China. Two temperature change metrics including temperature change between neighboring days (TCN) and diurnal temperature range (DTR) were used to assess the effects of temperature change exposure. Subgroup analyses were performed by gender, age and season. Besides, the attributable risk was calculated to evaluated the public health significance.

RESULTS

The overall exposure-response curves suggested that there were statistically significant associations between two temperature change metrics and the risk of TB admissions. The maximum lag-specific relative risk (RR) of TB admissions was 1.088 (95%CI: 1.012-1.171, lag 4 day) for exposing to large temperature drop (TCN= -4 °C) in winter. Besides, the overall cumulative risk of TB admissions increased continuously and peaked at a lag of 7 days (RR=1.350, 95%CI: 1.120-1.628). Subgroup analysis suggested that exposure to large temperature drop had an adverse effect on TB admissions among males, females and adults. Similarly, large level of DTR exposure (DTR=15 °C) in spring also increased the risk of TB admissions on lag 0 day (RR=1.039, 95%CI: 1.016-1.063), and the cumulative RRs peaked at a lag of 1 days (RR=1.029, 95%CI: 1.012-1.047). We also found that females and elderly people were more vulnerable to the large level of DTR exposure. Additionally, the assessment of attributable risk suggested that taking target measures for the upcoming large temperature drop (b-AF = 4.17%, 95% eCI: 1.24%, 7.22%, b-AN = 1195) may achieve great public health benefits for TB prevention.

CONCLUSION

This study suggests that ambient temperature change is associated with the risk of TB admissions. Besides, TCN may be a better predictor for the TB prevention and public health.

Epidemiological characteristics of pulmonary tuberculosis in Anhui Province, Eastern China from 2013 to 2018

OBJECTIVE

Pulmonary tuberculosis (TB) is a severe infectious respiratory disease, the burden of which remains high in China. To provide scientific evidence for developing more targeted prevention and control strategies, this study aimed to determine the incidence trends and explore the epidemiological characteristics of pulmonary TB in Anhui Province, Eastern China between 2013 and 2018.

METHODS

The retrospective study analyzed information regarding pulmonary TB cases reported by the National Infectious Disease Reporting System and census data collected from the Anhui Provincial Bureau of Statistics.

RESULTS

Overall, 211,892 cases of TB patients were reported in Anhui Province, China between 2013 and 2018, with an average annual reported incidence rate of 57.7 per 100,000 persons. A significant decrease in the incidence rate of pulmonary TB (p < 0.001) was observed during the study period. Men had a higher incidence rate of pulmonary TB than women (p < 0.001). The highest annual average reported incidence rate was 204.2 per 100,000 persons in those aged 70-74 years. The number of farmers with pulmonary TB, i.e., 155,415, accounted for 73.4% of all cases. Moreover, the peak period of reported cases was from January to March. Four cities along the Yangtze River-Anqing, Tongling, Chizhou, and Wuhu-reported significantly higher incidence rates of pulmonary TB than other cities (p < 0.001).

CONCLUSIONS

From 2013 to 2018, there was a significant decline in the incidence rate of pulmonary TB in Anhui Province, with peaks occurring from January to March. Prevention and control strategies targeting men, people aged 70-74 years, farmers, and the four cities along the Yangtze River should be strengthened.

Sociodemographic profiling of tuberculosis hotspots in Ethiopia, 2014-2017

BACKGROUND

Tuberculosis (TB) notification rates vary across regions in Ethiopia and districts within the Amhara Region. The Amhara Region is one of the main TB hotspot regions in the country. In this study we identified the spatial distribution of TB and characterized the sociodemographic factors of spatial clusters in the Amhara Region.

METHODS

An ecological spatial analysis of TB notifications from 2014 to 2017 was conducted to quantify the presence and location of spatial clusters of TB notifications at the district level within the Amhara Region. Global Moran's I statistics and local indicators of spatial association were used to explore the spatial clustering of TB notifications. Notifications from hotspots and low-risk districts were compared to identify significant sociodemographic factors using analysis of variance and Classification and Regression Tree analysis. The geographic information system and 'sp' packages of R software were used for spatial analysis.

RESULTS

From 2014 to 2017 the average notification rate of all forms of TB in the Amhara Region was 107/100 000 population (range 18-614 per 100 000 population). District-level TB notification rates were positively spatially autocorrelated, with Moran's I value ranging from 0.207 to 0.276 (p=0.01). Hotspot TB clusters were found in the northwest and central part of the region. The proportion of migrants (F(3,124)=23.21, p<0.001, d=1.4) was found to be the most important factor associated with hotspot TB clustering.

CONCLUSIONS

TB notification rates in the Amhara Region of Ethiopia over the past 4 y were significantly clustered. Distinguishing high-risk areas from low-risk areas and characterizing the proportion of migrants and other risk factors is important for targeted TB prevention and control in the region.

Does sunlight drive seasonality of TB in Vietnam? A retrospective environmental ecological study of tuberculosis seasonality in Vietnam from 2010 to 2015

BACKGROUND

Tuberculosis (TB) is a major global health burden, with an estimated quarter of the world's population being infected. The World Health Organization (WHO) launched the "End TB Strategy" in 2014 emphasising knowing the epidemic. WHO ranks Vietnam 12th in the world of high burden countries. TB spatial and temporal patterns have been observed globally with evidence of Vitamin D playing a role in seasonality. We explored the presence of temporal and spatial clustering of TB in Vietnam and their determinants to aid public health measures.

METHODS

Data were collected by the National TB program of Vietnam from 2010 to 2015 and linked to the following datasets: socio-demographic characteristics; climatic variables; influenza-like-illness (ILI) incidence; geospatial data. The TB dataset was aggregated by province and quarter. Descriptive time series analyses using LOESS regression were completed per province to determine seasonality and trend. Harmonic regression was used to determine the amplitude of seasonality by province. A mixed-effect linear model was used with province and year as random effects and all other variables as fixed effects.

RESULTS

There were 610,676 cases of TB notified between 2010 and 2015 in Vietnam. Heat maps of TB incidence per quarter per province showed substantial temporal and geospatial variation. Time series analysis demonstrated seasonality throughout the country, with peaks in spring/summer and troughs in autumn/winter. Incidence was consistently higher in the south, the three provinces with the highest incidence per 100,000 population were Tay Ninh, An Giang and Ho Chi Minh City. However, relative seasonal amplitude was more pronounced in the north. Mixed-effect linear model confirmed that TB incidence was associated with time and latitude. Of the demographic, socio-economic and health related variables, population density, percentage of those under 15 years of age, and HIV infection prevalence per province were associated with TB incidence. Of the climate variables, absolute humidity, average temperature and sunlight were associated with TB incidence.

CONCLUSION

Preventative public health measures should be focused in the south of Viet Nam where incidence is highest. Vitamin D is unlikely to be a strong driver of seasonality but supplementation may play a role in a package of interventions.

Short-term Effect of Air Pollution on Tuberculosis Based on Kriged Data: A Time-series Analysis

Tuberculosis (TB) has a very high mortality rate worldwide. However, only a few studies have examined the associations between short-term exposure to air pollution and TB incidence. Our objectives were to estimate associations between short-term exposure to air pollutants and TB incidence in Wuhan city, China, during the 2015–2016 period. We applied a generalized additive model to access the short-term association of air pollution with TB. Daily exposure to each air pollutant in Wuhan was determined using ordinary kriging. The air pollutants included in the analysis were particulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 micrometers (PM_2.5), PM with an aerodynamic diameter less than or equal to 10 micrometers (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ground-level ozone (O₃). Daily incident cases of TB were obtained from the Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Both single- and multiple-pollutant models were used to examine the associations between air pollution and TB. Seasonal variation was assessed by splitting the all-year data into warm (May–October) and cold (November–April) seasons. In the single-pollutant model, for a 10 μg/m³ increase in PM_2.5, PM₁₀, and O₃ at lag 7, the associated TB risk increased by 17.03% (95% CI: 6.39, 28.74), 11.08% (95% CI: 6.39, 28.74), and 16.15% (95% CI: 1.88, 32.42), respectively. In the multi-pollutant model, the effect of PM_2.5 on TB remained statistically significant, while the effects of other pollutants were attenuated. The seasonal analysis showed that there was not much difference regarding the impact of air pollution on TB between the warm season and the cold season. Our study reveals that the mechanism linking air pollution and TB is still complex. Further research is warranted to explore the interaction of air pollution and TB.

Bacteriologically-confirmed pulmonary tuberculosis in an Ethiopian prison: Prevalence from screening of entrant and resident prisoners

BACKGROUND

Pulmonary Tuberculosis (PTB) is a major health problem in prisons. Multiple studies of TB in regional Ethiopian prisons have assessed prevalence and risk factors but have not examined recently implemented screening programs for TB in prisons. This study compares bacteriologically-confirmed PTB (BC-PTB) prevalence in prison entrants versus residents and identifies risk factors for PTB in Kality prison, a large federal Ethiopian prison located in Addis Ababa, through a study of an enhanced TB screening program.

METHODS

Participating prisoners (n = 13,803) consisted of 8,228 entrants screened continuously and 5,575 residents screened in two cross-sectional waves for PTB symptoms, demographics, TB risk factors, and medical history. Participants reporting at least one symptom of PTB were asked to produce sputum which was examined by microscopy for acid-fast bacilli, Xpert MTB/RIF assay and MGIT liquid culture. Prevalence of BC-PTB, defined as evidence of Mycobacterium tuberculosis (MTB) in sputum by the above methods, was compared in entrants and residents for the study. Descriptive analysis of prevalence was followed by bivariate and multivariate analyses of risk factors.

RESULTS

Prisoners were mainly male (86%), young (median age 26 years) and literate (89%). Prevalence of TB symptoms by screening was 17% (2,334/13,803) with rates in residents >5-fold higher than entrants. Prevalence of BC-PTB detected by screening in participating prisoners was 0.16% (22/13,803). Prevalence in residents increased in the second resident screening compared to the first (R1 = 0.10% and R2 = 0.39%, p = 0.027), but remained higher than in entrants (4.3-fold higher during R1 and 3.1-fold higher during R2). Drug resistance (DR) was found in 38% (5/13) of culture-isolated MTB. Risk factors including being ever diagnosed with TB, history of TB contact and low Body Mass Index (BMI) (<18.5) were significantly associated with BC-PTB (p<0.05).

CONCLUSIONS

BC-PTB prevalence was strikingly lower than previously reported from other Ethiopian prisons. PTB appears to be transmitted within this prison based on its higher prevalence in residents than in entrants. Whether a sustained program of PTB screening of entrants and/or residents reduces prevalence of PTB in prisons is not clear from this study, but our findings suggest that resources should be prioritized to resident, rather than entrant, screening due to higher BC-PTB prevalence. Detection of multi- and mono-DR TB in both entrant and resident prisoners warrants regular screening for active TB and adoption of methods to detect drug resistance.

Delay effect and burden of weather-related tuberculosis cases in Rajshahi province, Bangladesh, 2007-2012

Tuberculosis (TB) is a potentially fatal infectious disease that continues to be a public health problem in Bangladesh. Each year in Bangladesh an estimated 70,000 people die of TB and 300,000 new cases are projected. It is important to understand the association between TB incidence and weather factors in Bangladesh in order to develop proper intervention programs. In this study, we examine the delayed effect of weather variables on TB occurrence and estimate the burden of the disease that can be attributed to weather factors. We used generalized linear Poisson regression models to investigate the association between weather factors and TB cases reported to the Bangladesh National TB control program between 2007 and 2012 in three known endemic districts of North-East Bangladesh. The associated risk of TB in the three districts increases with prolonged exposure to temperature and rainfall, and persisted at lag periods beyond 6 quarters. The association between humidity and TB is strong and immediate at low humidity, but the risk decreases with increasing lag. Using the optimum weather values corresponding to the lowest risk of infection, the risk of TB is highest at low temperature, low humidity and low rainfall. Measures of the risk attributable to weather variables revealed that weather-TB cases attributed to humidity is higher than that of temperature and rainfall in each of the three districts. Our results highlight the high linearity of temporal lagged effects and magnitudes of the burden attributable to temperature, humidity, and rainfall on TB endemics. The results can hopefully advise the Bangladesh National TB control program and act as a practical reference for the early warning of TB cases.

Vitamin D status and risk of incident tuberculosis disease: A nested case-control study, systematic review, and individual-participant data meta-analysis

BACKGROUND

Few studies have evaluated the association between preexisting vitamin D deficiency and incident tuberculosis (TB). We assessed the impact of baseline vitamins D levels on TB disease risk.

METHODS AND FINDINGS

We assessed the association between baseline vitamin D and incident TB in a prospective cohort of 6,751 HIV-negative household contacts of TB patients enrolled between September 1, 2009, and August 29, 2012, in Lima, Peru. We screened for TB disease at 2, 6, and 12 months after enrollment. We defined cases as household contacts who developed TB disease at least 15 days after enrollment of the index patient. For each case, we randomly selected four controls from among contacts who did not develop TB disease, matching on gender and year of age. We also conducted a one-stage individual-participant data (IPD) meta-analysis searching PubMed and Embase to identify prospective studies of vitamin D and TB disease until June 8, 2019. We included studies that assessed vitamin D before TB diagnosis. In the primary analysis, we defined vitamin D deficiency as 25-(OH)D < 50 nmol/L, insufficiency as 50-75 nmol/L, and sufficiency as >75nmol/L. We estimated the association between baseline vitamin D status and incident TB using conditional logistic regression in the Lima cohort and generalized linear mixed models in the meta-analysis. We further defined severe vitamin D deficiency as 25-(OH)D < 25 nmol/L and performed stratified analyses by HIV status in the IPD meta-analysis. In the Lima cohort, we analyzed 180 cases and 709 matched controls. The adjusted odds ratio (aOR) for TB risk among participants with baseline vitamin D deficiency compared to sufficient vitamin D was 1.63 (95% CI 0.75-3.52; p = 0.22). We included seven published studies in the meta-analysis and analyzed 3,544 participants. In the pooled analysis, the aOR was 1.48 (95% CI 1.04-2.10; p = 0.03). The aOR for severe vitamin D deficiency was 2.05 (95% CI 0.87-4.87; p trend for decreasing 25-(OH)D levels from sufficient vitamin D to severe deficiency = 0.02). Among 1,576 HIV-positive patients, vitamin D deficiency conferred a 2-fold (aOR 2.18, 95% CI 1.22-3.90; p = 0.01) increased risk of TB, and the aOR for severe vitamin D deficiency compared to sufficient vitamin D was 4.28 (95% CI 0.85-21.45; p = 0.08). Our Lima cohort study is limited by the short duration of follow-up, and the IPD meta-analysis is limited by the number of possible confounding covariates available across all studies.

CONCLUSION

Our findings suggest vitamin D predicts TB disease risk in a dose-dependent manner and that the risk of TB disease is highest among HIV-positive individuals with severe vitamin D deficiency. Randomized control trials are needed to evaluate the possible role of vitamin D supplementation on reducing TB disease risk.

Temporal trends analysis of tuberculosis morbidity in mainland China from 1997 to 2025 using a new SARIMA-NARNNX hybrid model

OBJECTIVE

Tuberculosis (TB) remains a major deadly threat in mainland China. Early warning and advanced response systems play a central role in addressing such a wide-ranging threat. The purpose of this study is to establish a new hybrid model combining a seasonal autoregressive integrated moving average (SARIMA) model and a non-linear autoregressive neural network with exogenous input (NARNNX) model to understand the future epidemiological patterns of TB morbidity.

METHODS

We develop a SARIMA-NARNNX hybrid model for forecasting future levels of TB incidence based on data containing 255 observations from January 1997 to March 2018 in mainland China, and the ultimate simulating and forecasting performances were compared with the basic SARIMA, non-linear autoregressive neural network (NARNN) and error-trend-seasonal (ETS) approaches, as well as the SARIMA-generalised regression neural network (GRNN) and SARIMA-NARNN hybrid techniques.

RESULTS

In terms of the root mean square error, mean absolute error, mean error rate and mean absolute percentage error, the identified best-fitting SARIMA-NARNNX combined model with 17 hidden neurons and 4 feedback delays had smaller values in both in-sample simulating scheme and the out-of-sample forecasting scheme than the preferred single SARIMA(2,1,3)(0,1,1)₁₂ model, a NARNN with 19 hidden neurons and 6 feedback delays and ETS(M,A,A), and the best-performing SARIMA-GRNN and SARIMA-NARNN models with 32 hidden neurons and 6 feedback delays. Every year, there was an obvious high-risk season for the notified TB cases in March and April. Importantly, the epidemic levels of TB from 2006 to 2017 trended slightly downward. According to the projection results from 2018 to 2025, TB incidence will continue to drop by 3.002% annually but will remain high.

CONCLUSIONS

The new SARIMA-NARNNX combined model visibly outperforms the other methods. This hybrid model should be used for forecasting the long-term epidemic patterns of TB, and it may serve as a beneficial and effective tool for controlling this disease.

Season and size of urban particulate matter differentially affect cytotoxicity and human immune responses to Mycobacterium tuberculosis

Exposure to air pollution particulate matter (PM) and tuberculosis (TB) are two of the leading global public health challenges affecting low and middle income countries. An estimated 4.26 million premature deaths are attributable to household air pollution and an additional 4.1 million to outdoor air pollution annually. Mycobacterium tuberculosis (M.tb) infects a large proportion of the world's population with the risk for TB development increasing during immunosuppressing conditions. There is strong evidence that such immunosuppressive conditions develop during household air pollution exposure, which increases rates of TB development. Exposure to urban air pollution has been shown to alter the outcome of TB therapy. Here we examined whether in vitro exposure to urban air pollution PM alters human immune responses to M.tb. PM2.5 and PM10 (aerodynamic diameters <2.5μm, <10μm) were collected monthly from rainy, cold-dry and warm-dry seasons in Iztapalapa, a highly populated TB-endemic municipality of Mexico City with elevated outdoor air pollution levels. We evaluated the effects of seasonality and size of PM on cytotoxicity and antimycobacterial host immunity in human peripheral blood mononuclear cells (PBMC) from interferon gamma (IFN-γ) release assay (IGRA)+ and IGRA- healthy study subjects. PM10 from cold-dry and warm-dry seasons induced the highest cytotoxicity in PBMC. With the exception of PM2.5 from the cold-dry season, pre-exposure to all seasonal PM reduced M.tb phagocytosis by PBMC. Furthermore, M.tb-induced IFN-γ production was suppressed in PM2.5 and PM10-pre-exposed PBMC from IGRA+ subjects. This observation coincides with the reduced expression of M.tb-induced T-bet, a transcription factor regulating IFN-γ expression in T cells. Pre-exposure to PM10 compared to PM2.5 led to greater loss of M.tb growth control. Exposure to PM2.5 and PM10 collected in different seasons differentially impairs M.tb-induced human host immunity, suggesting biological mechanisms underlying altered M.tb infection and TB treatment outcomes during air pollution exposures.

Risk factors for active tuberculosis in 938 QuantiFERON-positive schoolchildren in Mongolia: a community-based cross-sectional study

BACKGROUND

There is controversy regarding the relative influence of 'exogenous' versus 'endogenous' factors on the risk of progression from latent tuberculosis infection to active tuberculosis (TB) disease in children.

METHODS

We conducted a cross-sectional analysis to identify risk factors for active tuberculosis in QuantiFERON®-TB Gold (QFT-G)-positive children aged 6-13 years attending 18 schools in Ulaanbaatar, Mongolia. Children underwent clinical and radiological screening for active tuberculosis, and data relating to potential risk factors for disease progression were collected by questionnaire and determination of serum 25-hydroxyvitamin D (25[OH]D) concentrations. Risk ratios were calculated using generalized estimating equations with adjustment for potential confounders.

RESULTS

129/938 (13.8%) QFT-positive children were diagnosed with active tuberculosis. Risk of active tuberculosis was independently associated with household exposure to pulmonary TB (adjusted risk ratio [aRR] 2.40, 95% CI 1.74 to 3.30, P < 0.001), month of sampling (adjusted risk ratio [aRR] for March-May vs. June-November 3.31, 95% CI 1.63 to 6.74, P < 0.001; aRR for December-February vs. June-November 2.53, 95% CI 1.23 to 5.19, P = 0.01) and active smoking by the child (aRR 5.23, 95% CI 2.70 to 10.12, P < 0.001). No statistically significant independent association was seen for age, sex, socio-economic factors, presence of a Bacillus Calmette-Guérin (BCG) scar, tobacco exposure or vitamin D status.

CONCLUSIONS

Household exposure to active TB, winter or spring season and active smoking were independently associated with risk of active tuberculosis in QFT-positive children. Our findings highlight the potentially high yield of screening child household contacts of infectious index cases for active tuberculosis in low- and middle-income countries.

Development and validation of a predictive ecological model for TB prevalence

Background

Nationally representative tuberculosis (TB) prevalence surveys provide invaluable empirical measurements of TB burden but are a massive and complex undertaking. Therefore, methods that capitalize on data from these surveys are both attractive and imperative. The aim of this study was to use existing TB prevalence estimates to develop and validate an ecological predictive statistical model to indirectly estimate TB prevalence in low- and middle-income countries without survey data.

Methods

We included national and subnational estimates from 30 nationally representative surveys and 2 district-level surveys in India, resulting in 50 data points for model development (training set). Ecological predictors included TB notification and programmatic data, co-morbidities and socio-environmental factors extracted from online data repositories. A random-effects multivariable binomial regression model was developed using the training set and was used to predict bacteriologically confirmed TB prevalence in 63 low- and middle-income countries across Africa and Asia in 2015.

Results

Out of the 111 ecological predictors considered, 14 were retained for model building (due to incompleteness or collinearity). The final model retained for predictions included five predictors: continent, percentage retreated cases out of all notified, all forms TB notification rates per 100 000 population, population density and proportion of the population under the age of 15. Cross-fold validations in the training set showed very good average fit (R-sq = 0.92).

Conclusion

Predictive ecological modelling is a useful complementary approach to indirectly estimating TB burden and can be considered alongside other methods in countries with limited robust empirical measurements of TB among the general population.

Temporal Cross-Correlations between Ambient Air Pollutants and Seasonality of Tuberculosis: A Time-Series Analysis

The associations between ambient air pollutants and tuberculosis seasonality are unclear. We assessed the temporal cross-correlations between ambient air pollutants and tuberculosis seasonality. Monthly tuberculosis incidence data and ambient air pollutants (PM_2.5, PM₁₀, carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂)) and air quality index (AQI) from 2013 to 2017 in Shanghai were included. A cross-correlogram and generalized additive model were used. A 4-month delayed effect of PM_2.5 (0.55), PM₁₀ (0.52), SO₂ (0.47), NO₂ (0.40), CO (0.39), and AQI (0.45), and a 6-month delayed effect of O₃ (−0.38) on the incidence of tuberculosis were found. The number of tuberculosis cases increased by 8%, 4%, 18%, and 14% for a 10 μg/m³ increment in PM_2.5, PM₁₀, SO₂, and NO₂; 4% for a 10 unit increment in AQI; 8% for a 0.1 mg/m³ increment in CO; and decreased by 4% for a 10 μg/m³ increment in O₃. PM_2.5 concentrations above 50 μg/m³, 70 μg/m³ for PM₁₀, 16 μg/m³ for SO₂, 47 μg/m³ for NO₂, 0.85 mg/m³ for CO, and 85 for AQI, and O₃ concentrations lower than 95 μg/m³ were positively associated with the incidence of tuberculosis. Ambient air pollutants were correlated with tuberculosis seasonality. However, this sort of study cannot prove causality.

Seasonality of childhood tuberculosis cases in Kampala, Uganda, 2010-2015

BACKGROUND

Seasonality in tuberculosis (TB) has been described, especially in children. However, few studies have assessed seasonality of TB in the equatorial region, and none in children.

OBJECTIVES

To assess for seasonality of childhood TB cases in Kampala, Uganda, and determine the role of temperature, rainfall patterns, and influenza cases on TB diagnoses.

METHODS

We retrospectively analyzed demographic and clinical data of children (under 15 years) diagnosed with TB at a pediatric TB clinic in Kampala, Uganda from 2010 to 2015. We performed decomposition analysis of the monthly case time series to assess seasonality. We compared monthly mean plots and performed Poisson regression to assess any association between TB diagnoses and temperature, rainfall, and influenza.

RESULTS

Of the 713 childhood TB cases diagnosed at the clinic, 609 (85%) were clinically diagnosed and 492 (69%) were pulmonary cases. There were minimal monthly variations in TB cases, with a trough in December and peaks in July and October, but there was no significant seasonality. Temperature variations did not show a clear pattern with TB diagnoses. Rainfall alternated with TB diagnoses in the first half of the year, but then overlapped in the second half and was significantly associated with TB diagnoses. Influenza cases were significantly related to TB diagnoses with (β = 0.05, 95% CI 0.01 to 0.09, p = 0.01) or without (β = 0.06, 95% CI 0.01 to 0.1, p = 0.01) rainfall, and had particular overlap with pulmonary TB cases.

CONCLUSIONS

Seasonal variations in childhood TB diagnoses were non-significant. Temperature did not have a clear pattern with TB diagnoses, but rainfall and influenza cases correlated with the primarily clinically diagnosed childhood TB cases.

Time-series analysis of geographically specific monthly number of newly registered cases of active tuberculosis in Japan

Background

Understanding seasonality of tuberculosis (TB) epidemics may lead to identify potentially modifiable risk factors. Studies conducted outside Japan have found seasonal variation among reported TB cases, with peaks in spring and summer and low prevalence in fall and winter. One hypothesis regarding spring or summer peaks in TB epidemics is that TB transmission likely increases in winter because of indoor crowding and poor ventilation, with development of primary TB among socially vulnerable people in spring and summer. Another plausible explanation is that vitamin D deficiency in winter depresses immunity, increasing the TB reactivation risk in these seasons. Previous studies suggest latitude-dependent factors, including reduced winter sunlight and its effect on vitamin D levels. Here, we investigated mechanisms of seasonality in TB epidemics in Japan, according to the effects of crowding and latitude.

Methods

We used time-series analysis consisting of spectral analysis and least-squares method, to analyse geographically specific monthly number of newly registered cases of all forms of active TB in all 47 prefectures of Japan during 1998–2015.

Results

In all power spectral densities for the 47 prefectures, spectral lines were observed at frequency positions corresponding to a 1-year cycle. The degree of this seasonality was associated with population density. We did not detect greater amplitude of seasonality at higher latitudes, suggesting that latitude-dependent factors, including reduced winter sunlight and its potential effect on vitamin D levels, do not contribute significantly to seasonality in Japan.

Discussion and conclusion

In districts with high population density, measures are needed to address two specific types of active infection risk in adolescents and middle-aged adults: (i) public transport use, and (ii) irregular employment with no periodic medical examinations. To control active TB epidemics, investigating periodic structures in the temporal patterns of active TB in each district and each age group is important.