A scoping review on climate change and tuberculosis

Transgression of planetary boundaries and the effects on child health through an infectious diseases lens

PURPOSE OF REVIEW

Life on earth, as we know it, is changing. The likelihood of more frequent pandemics and disease outbreaks is something that current global healthcare infrastructure is ill equipped to navigate. Human activity is forcing our planet into a new geologic epoch, the Anthropocene, which is typified by increased uncertainty resulting from human disruption of earth's life-giving ecosystems. Plagues and pandemics have always been unfortunate partners to periods of disruption, as they will be again if the frequency and severity of climate and conflict-mediated disasters increase in coming years. If we continue to exceed and degrade the planetary boundaries that protect human health, our children and their children will reap the consequences.

RECENT FINDINGS

Scientists have defined nine 'safe operating' planetary boundaries for life in all its glorious diversity to thrive on planet earth. Recent evidence suggests that six of these nine boundaries have already been transgressed, but the potential implications for these transgressions upon child health is not well articulated. We highlight how contravention of these boundaries will impact infectious disease risk and humans' ability to survive and thrive. We reflect specifically on how paediatricians are called upon to speak up for the most vulnerable members of our species, young children and as yet unborn future generations.

SUMMARY

Post COVID-19 initiatives to improve pandemic preparedness and response are certainly warranted, but pandemic prevention should include committed efforts not to exceed safe planetary boundaries. Willingly exceeding these boundaries has deep moral consequences that are poorly articulated by current ethical frameworks. Paediatricians are best placed to develop and champion the neglected 'third dimension' of medical ethics, recognizing the moral imperative to protect the long-term best interests of children and future generations.

Coinfections in Tuberculosis in Low- and Middle-Income Countries: Epidemiology, Clinical Implications, Diagnostic Challenges, and Management Strategies-A Narrative Review

Tuberculosis (TB) continues to be a major public health challenge in low- and middle-income countries (LMICs), where high burdens of coinfections exacerbate the disease's impact. In 2023, an estimated 8.2 million people were newly diagnosed with tuberculosis worldwide, reflecting an increase from 7.5 million in 2022 and 7.1 million in 2019. In LMICs, limited access to healthcare, inadequate nutrition, and poor living conditions contribute to higher coinfection rates among TB patients, leading to delayed diagnosis and treatment, which in turn exacerbates disease severity and facilitates transmission. This narrative review synthesizes the epidemiology, clinical implications, diagnostic challenges, and management strategies related to TB coinfections with viral pathogens including HIV, SARS-CoV-2, and influenza, bacteria such as Streptococcus pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae, and Pseudomonas aeruginosa, fungi such as Aspergillus and Candida species, and parasites. This review highlights that overlapping symptoms, immune system compromise, and socioeconomic barriers in LMICs lead to delayed diagnoses and suboptimal treatment outcomes, while also addressing the challenges of managing drug interactions particularly in HIV-TB coinfections and underscoring the need for integrated diagnostic approaches, improved treatment regimens, and strengthened healthcare systems, thereby consolidating current evidence to inform future research priorities and policy interventions aimed at reducing the overall burden of TB and its coinfections in resource-limited settings.

Climate change and tuberculosis: an analytical framework

Climate change is likely to exacerbate a range of determinants which drive tuberculosis, the world's leading infectious disease killer. However, tuberculosis is often neglected in wider climate health discussions. Commissioned by the World Health Organization, we developed an analytical framework outlining potential causal relationships between climate change and tuberculosis. We drew on existing knowledge of tuberculosis determinants, identified which are likely to be sensitive to the effects of climate change, and conceptualised the mechanistic pathways through which this might occur. We collated evidence for these pathways through literature reviews. Our reviews found no studies directly linking climate change and tuberculosis, warranting research to build evidence for action. The available evidence supports the existence of plausible links between climate change and tuberculosis, and highlights the need to include tuberculosis in climate risk adaptation and mitigation programmes, and climate-resilient funding and response mechanisms. Further evidence is urgently needed to quantify the effects of climate change on tuberculosis.

Health system and environmental factors affecting global progress towards achieving End TB targets between 2015 and 2020

Background

Health system and environmental factors play a significant role in achieving the World Health Organization (WHO) End Tuberculosis (TB) targets. However, quantitative measures are scarce or non-existent at a global level. We aimed to measure the progress made towards meeting the global End TB milestones from 2015 to 2020 and identify health system and environmental factors contributing to the success.

Methods

We obtained data from ten different online data repositories and used principal component analysis to create domain-specific health system performance measures. We used radar charts and dumbbell plots to show the country's progress in ending TB with their health systems. Lastly, we used a linear regression model to identify key health systems and environmental predictors of the percent reduction in TB incidence and mortality.

Results

There was a high variation in TB incidence and mortality reduction between countries and WHO regions. Of all countries included, 75 (39.3%) achieved more than a 20% reduction in TB incidence between 2015 and 2020. However, only 31 (16.2%) reached a 35% reduction in TB mortality. The European Region achieved the highest incidence reduction, exceeding the 2020 milestone with a 25% reduction. The African Region also made notable progress, achieving an 18% mortality reduction despite its relatively poor health systems. Health system factors, such as TB financing, TB-specific health service delivery, access to medicine, and governance, were significantly associated with TB mortality reduction between 2015 and 2020. Environmental factors, such as average annual temperature and air particulate matter concentration, were found to have a significant negative effect on TB incidence and mortality reduction.

Conclusions

Weak health systems were identified as major barriers to achieving the End TB milestones in most high-burden countries. Hence, strengthening health systems with a special focus on TB financing, service delivery, and access to medicine in these countries should be prioritised to achieve global TB mortality reduction targets. Countries should follow WHO's air quality guidelines and rapidly reduce carbon dioxide and other greenhouse gas emissions to mitigate the impact of environmental factors.

Google trend analysis of the Indian population reveals a panel of seasonally sensitive comorbid symptoms with implications for monitoring the seasonally sensitive human population

Seasonal variations in the environment induce observable changes in the human physiological system and manifest as various clinical symptoms in a specific human population. Our earlier studies predicted four global severe seasonal sensitive comorbid lifestyle diseases (SCLDs), namely, asthma, obesity, hypertension, and fibrosis. Our studies further indicated that the SCLD category of the human population may be maladapted or unacclimatized to seasonal changes. The current study aimed to explore the major seasonal symptoms associated with SCLD and evaluate their seasonal linkages via Google Trends (GT). We used the Human Disease Symptom Network (HSDN) to dissect common symptoms of SCLD. We then exploited medical databases and medical literature resources in consultation with medical practitioners to narrow down the clinical symptoms associated with four SCLDs, namely, pulmonary hypertension, pulmonary fibrosis, asthma, and obesity. Our study revealed a strong association of 12 clinical symptoms with SCLD. Each clinical symptom was further subjected to GT analysis to address its seasonal linkage. The GT search was carried out in the Indian population for the period from January 2015-December 2019. In the GT analysis, 11 clinical symptoms were strongly associated with Indian seasonal changes, with the exception of hypergammaglobulinemia, due to the lack of GT data in the Indian population. These 11 symptoms also presented sudden increases or decreases in search volume during the two major Indian seasonal transition months, namely, March and November. Moreover, in addition to SCLD, several seasonally associated clinical disorders share most of these 12 symptoms. In this regard, we named these 12 symptoms the "seasonal sensitive comorbid symptoms (SSC)" of the human population. Further clinical studies are needed to verify the utility of these symptoms in screening seasonally maladapted human populations. We also warrant that clinicians and researcher be well aware of the limitations and pitfalls of GT before correlating the clinical outcome of SSC symptoms with GT.

Environmental stressors and zoonoses in the Arctic: Learning from the past to prepare for the future

The risk of zoonotic disease transmission from animals to humans is elevated for people in close contact with domestic and wild animals. About three-quarters of all known human infectious diseases are zoonotic, and potential health impacts of these diseases are higher where infectious disease surveillance and access to health care and public health services are limited. This is especially the case for remote circumarctic regions, where drivers for endemic, emerging, and re-emerging zoonotic diseases include anthropogenic influences, such as pollution by long-range transport of industrial chemicals, climate change, loss of biodiversity and ecosystem alterations. In addition to these, indirect effects including natural changes in food web dynamics, appearance of invasive species and thawing permafrost also affect the risk of zoonotic disease spill-over. In other words, the Arctic represents a changing world where pollution, loss of biodiversity and habitat, and maritime activity are likely driving forward occurrence of infectious diseases. As a broad international consortium with a wide range of expertise, we here describe a selection of case studies highlighting the importance of a One Health approach to zoonoses in the circumarctic, encompassing human health, animal health, and environmental health aspects. The cases highlight critical gaps in monitoring and current knowledge, focusing on environmental stressors and lifestyle factors, and they are examples of current occurrences in the Arctic that inform on critically needed actions to prepare us for the future. Through these presentations, we recommend measures to enhance awareness and management of existing and emerging zoonoses with epidemic and pandemic potential while also focusing on the impacts of various environmental stressors and lifestyle factors on zoonoses in the Arctic.

Exploring the short-term effects of extreme temperatures on tuberculosis incidence in Shantou, China: a Coastal City perspective

OBJECTIVE

Coastal cities, due to their proximity to coastlines and unique climatic conditions, face growing challenges from extreme temperature events associated with climate change. Research on the impact of extreme temperatures on tuberculosis (TB) in these cities is limited, and findings from different regions lack consensus. This study focuses on Shantou, a coastal city in China, to investigate the influence of extreme temperatures on TB within this distinctive geographical context.

METHODS

Distributed Lag Non-Linear Models (DLNM) were employed to evaluate the effect of extreme temperatures on TB incidence risk in Shantou, a coastal city in China, spanning from 2014 to 2021. Daily TB case data were provided by the Shantou Tuberculosis Prevention and Control Institute. Daily meteorological information was sourced from the Reliable Prognosis website, while daily air pollutant data were obtained from the China Air Quality Online Monitoring and Analysis Platform.

RESULTS

The study revealed a significant association between extreme temperatures and TB incidence, with the impact peaking at a lag of 27 days after exposure. Notably, extreme cold temperatures led to a temporary decrease in TB incidence with a lag of 1-2 days. Subgroup analysis indicated that males had a notably higher risk of TB under extreme temperature conditions compared to females. Additionally, individuals aged 65 years and above showed a significant cumulative effect in such conditions.

CONCLUSIONS

This research enhances our comprehension of the effects of extreme temperatures on TB in coastal cities and carries substantial public health implications for TB prevention in China.

Exploring the influence of environmental indicators and forecasting influenza incidence using ARIMAX models

Background

Influenza is a respiratory infection that poses a significant health burden worldwide. Environmental indicators, such as air pollutants and meteorological factors, play a role in the onset and propagation of influenza. Accurate predictions of influenza incidence and understanding the factors influencing it are crucial for public health interventions. Our study aims to investigate the impact of various environmental indicators on influenza incidence and apply the ARIMAX model to integrate these exogenous variables to enhance the accuracy of influenza incidence predictions.

Method

Descriptive statistics and time series analysis were employed to illustrate changes in influenza incidence, air pollutants, and meteorological indicators. Cross correlation function (CCF) was used to evaluate the correlation between environmental indicators and the influenza incidence. We used ARIMA and ARIMAX models to perform predictive analysis of influenza incidence.

Results

From January 2014 to September 2023, a total of 21,573 cases of influenza were reported in Fuzhou, with a noticeable year-by-year increase in incidence. The peak of influenza typically occurred around January each year. The results of CCF analysis showed that all 10 environmental indicators had a significant impact on the incidence of influenza. The ARIMAX(0, 0, 1) (1, 0, 0)12 with PM10(lag5) model exhibited the best prediction performance, as indicated by the lowest AIC, AICc, and BIC values, which were 529.740, 530.360, and 542.910, respectively. The model achieved a fitting RMSE of 2.999 and a predicting RMSE of 12.033.

Conclusion

This study provides insights into the impact of environmental indicators on influenza incidence in Fuzhou. The ARIMAX(0, 0, 1) (1, 0, 0)12 with PM10(lag5) model could provide a scientific basis for formulating influenza control policies and public health interventions. Timely prediction of influenza incidence is essential for effective epidemic control strategies and minimizing disease transmission risks.

HIV in Eswatini: Climate Change Impacts and Adaptation Strategies

Purpose of Review

This review assessed the impact of climate change on HIV transmission and HIV care of children and adults in Eswatini, and what adaptation strategies can mitigate these impacts.

Recent Findings

The HIV crisis in Eswatini persists alongside the climate emergency, increasing poor health outcomes in individuals living with HIV. Although there is no clinical evidence of a direct influence of climate change on the biological effect of HIV, changing weather patterns have an effect on the livelihoods and sustenance of children, adults, and caregivers, which may consequently increase the likelihood of HIV transmission and disrupt HIV care.

Summary

Drought conditions-expected to increase with climate change-coupled with existing food insecurity and poverty are the main pathways linking HIV and climate change in Eswatini. Other climate-driven concerns for HIV treatment and care in Eswatini include heat waves, wildfires, floods, and storms.

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.

Climate Change and Human Health in Africa in Relation to Opportunities to Strengthen Mitigating Potential and Adaptive Capacity: Strategies to Inform an African "Brains Trust"

Background

Africa faces diverse and complex population/human health challenges due to climate change. Understanding the health impacts of climate change in Africa in all its complexity is essential for implementing effective strategies and policies to mitigate risks and protect vulnerable populations. This study aimed to outline the major climate change-related health impacts in Africa in the context of economic resilience and to seek solutions and provide strategies to prevent or reduce adverse effects of climate change on human health and well-being in Africa.

Methods

For this narrative review, a literature search was conducted in the Web of Science, Scopus, CAB Abstracts, MEDLINE and EMBASE electronic databases. We also searched the reference lists of retrieved articles for additional records as well as reports. We followed a conceptual framework to ensure all aspects of climate change and health impacts in Africa were identified.

Results

The average temperatures in all six eco-regions of Africa have risen since the early twentieth century, and heat exposure, extreme events, and sea level rise are projected to disproportionately affect Africa, resulting in a larger burden of health impacts than other continents. Given that climate change already poses substantial challenges to African health and well-being, this will necessitate significant effort, financial investment, and dedication to climate change mitigation and adaptation. This review offers African leaders and decision-makers data-driven and action-oriented strategies that will ensure a more resilient healthcare system and safe, healthy populations-in ways that contribute to economic resiliency.

Conclusions

The urgency of climate-health action integrated with sustainable development in Africa cannot be overstated, given the multiple economic gains from reducing current impacts and projected risks of climate change on the continent's population health and well-being. Climate action must be integrated into Africa's development plan to meet the Sustainable Development Goals, protect vulnerable populations from the detrimental effects of climate change, and promote economic development.

An investigation of the effects of meteorological factors on the incidence of tuberculosis

To explore the influence of meteorological factors on the incidence of tuberculosis (TB) in Yingjisha County, Kashgar Region, Xinjiang, and to provide a scientific basis for the prevention and control of TB. The Spearman correlation analysis and distribution lag nonlinear model analysis were conducted on the number of daily reported cases of TB from 2016 to 2023 to study the association effect of various meteorological factors and the daily incidence number of TB in Yingjisha County. A total of 13,288 TB cases were reported from January 2016 to June 2023, and June to October is the peak period of annual TB incidence. Spearman correlation analysis revealed that average daily temperature (AT) and average daily wind speed (WS) were positively correlated with TB incidence (rAT = 0.110, rWS = 0.090); and average daily relative humidity (RH) and TB incidence was negatively correlated (rRH = - 0.093). When AT was - 15 °C, the RR reached a maximum of 2.20 (95% CI: 0.77-6.29) at a lag of 21 days. When RH was 92%, the RR reached a maximum of 1.05 (95% CI: 0.92-1.19) at a lag of 6 days. When WS was 5.2 m/s, the RR reached a maximum of 1.30 (95% CI: 0.78-2.16) at a lag of 16 days. There is a non-linearity and a certain lag between meteorological factors and the occurrence and prevalence of TB in the population, which is mainly manifested in the fact that the risk of incidence of TB decreases with the increase of the daily AT, has a hazardous effect within a certain range of humidity as the average daily RH rises, and gradually increases with the increase of the average daily WS. Local residents are advised to pay attention to climate change so as to take appropriate preventive measures, especially women and middle and old age group should pay close attention to climate change and add more clothes in time, minimise travelling in hazy weather and windy and sandy weather, maintain good nutrition, adequate sleep and moderate exercise in daily life to enhance their immunity, wash hands frequently and ventilate the air, and try to avoid staying in humid and confined spaces in order to reduce the risk of latent TB patients developing the disease.

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.

A methodological framework for ranking communicable and non-communicable diseases due to climate change - A focus on Ireland

There is currently a significant global focus from the public health community on addressing climate-related public health issues. Globally we are witnessing geological shifts, extreme weather events, and the associated incidents that may have a significant human health impact. These include unseasonable weather, heavy rainfall, global sea-level rise and flooding, droughts, tornados, hurricanes, and wildfires. Climate change can have a direct and indirect health impact. The global challenge of climate change requires global preparedness for potential human health effects due to climate change, including vigilance for diseases carried by vectors, foodborne and waterborne diseases, deteriorated air quality, heat stress, mental health, and potential disasters. Therefore, it is essential to identify and prioritise the consequences of climate change to become future-ready. This proposed methodological framework aimed to develop an innovative modelling method using the 'Disability-Adjusted Life Year (DALY)', to rank potential direct and indirect human health impacts (communicable and non-communicable diseases) of climate change. This approach aims to ensure food safety, including water, in the wake of climate change. The novelty of the research will come from developing models with spatial mapping (Geographic Information System or GIS), which will also consider the influence of climatic variables, geographical differences in exposure and vulnerability and regulatory control on feed/food quality and abundance, range, growth, and survival of selected microorganisms. In addition, the outcome will identify and assess emerging modelling techniques and computational-efficient tools to overcome current limitations in climate change research on human health and food safety and to understand uncertainty propagation using the Monte Carlo simulation method for future climate change scenarios. It is envisaged that this research work will contribute significantly to developing a lasting network and critical mass on a national scale. It will also provide a template to implement from a core centre of excellence in other jurisdictions.

Warmer water, high light intensity, lithium and microplastics: Dangerous environmental combinations to zooplankton and Global Health?

Nowadays there is a high concern about the combined effects of global warming and emerging environmental contaminants with significant increasing trends of use, such as lithium (Li) and microplastics (MPs), both on wildlife and human health. Therefore, the effects of high light intensity (26,000 lx) or warmer water temperature (25 °C) on the long-term toxicity of Li and mixtures of Li and MPs (Li-MPs mixtures) were investigated using model populations of the freshwater zooplankton species Daphnia magna. Three 21-day bioassays were done in the laboratory at the following water temperatures and light intensities: (i) 20 °C/10830 lx; (ii) 20 °C/26000 lx (high light intensity); (iii) 25 °C/10830 lx (warmer temperature). Based on the 21-day EC50s on reproduction, high light intensity increased the reproductive toxicity of Li and Li-MPs mixtures by ~1.3 fold; warmer temperature increased the toxicity of Li by ~1.2 fold, and the toxicity of Li-MPs mixtures by ~1.4 fold based on the concentration of Li, and by ~2 fold based on the concentrations of MPs. At high light intensity, Li (0.04 mg/L) and Li-MPs mixtures (0.04 Li + 0.09 MPs mg/L) reduced the population fitness by 32 % and 41 %, respectively. Warmer temperature, Li (0.05 mg/L) and Li-MPs mixtures (0.05 Li + 0.09 MPs mg/L) reduced it by 63 % and 71 %, respectively. At warmer temperature or high light intensity, higher concentrations of Li and Li-MPs mixtures lead to population extinction. Based on the population growth rate and using data of bioassays with MPs alone done simultaneously, Li and MPs interactions were antagonistic or synergistic depending on the scenario. High light intensity and chemical stress generally acted synergistically. Warmer temperature and chemical stress always acted synergistically. These findings highlight the threats of long-term exposure to Li and Li-MPs mixtures to freshwater zooplankton and Global Health in a warmer world.

Analysis of the effect of temperature on tuberculosis incidence by distributed lag non-linear model in Kashgar city, China

The aim of this study was to explore the effect of temperature on tuberculosis (TB) incidence using the distributed lag non-linear model (DLNM) from 2017 to 2021 in Kashgar city, the region with higher TB incidence than national levels, and assist public health prevention and control measures. From January 2017 to December 2021, a total of 8730 cases of TB were reported, with the higher incidence of male than that of female. When temperature was below 1 °C, it was significantly correlated with TB incidence compared to the median observed temperature (15 °C) at lag 7, 14, and 21, and lower temperatures showed larger RR (relative risk) values. High temperature produced a protective effect on TB transmission, and higher temperature from 16 to 31 °C has lower RR. In discussion stratified by gender, the maximum RRs were achieved for both male group and female group at - 15 °C with lag 21, reporting 4.28 and 2.02, respectively. At high temperature (higher than 20 °C), the RR value of developing TB for female group was significantly larger than 1. In discussion stratified by age, the maximum RRs were achieved for all age groups (≤ 35, 36-64, ≥ 65) at - 15 °C with lag 21, reporting 3.20, 2.07, and 3.45, respectively. When the temperature was higher than 20 °C, the RR of the 36-64-year-old group and the ≥ 65-year-old group was significantly larger than 1 at lag 21, while significantly smaller than 1 for cumulative RR at lag 21, reporting 0.11, 95% confidence interval (CI) (0.01, 0.83) and 0.06, 95% CI (0.01, 0.44), respectively. In conclusion, low temperature, especially in extreme level, acts as a high-risk factor inducing TB transmission in Kashgar city. Males exhibit a significantly higher RR of developing TB at low temperature than female, as well as the elderly group in contrast to the young or middle-aged groups. High temperature has a protective effect on TB transmission in the total population, but female and middle-aged and elderly groups are also required to be alert to the delayed RR induced by it.

The impact of climate change on the risk factors for tuberculosis: A systematic review

BACKGROUND

Tuberculosis (TB) continues to pose a major public health risk in many countries. The current incidence of disease exceeds guidelines proposed by the World Health Organisation and United Nations. Whilst the relationship between climate change and TB has surfaced in recent literature, it remains neglected in global agendas. There is a need to acknowledge TB as a climate-sensitive disease to facilitate its eradication.

OBJECTIVE

To review epidemiological and prediction model studies that explore how climate change may affect the risk factors for TB, as outlined in the Global Tuberculosis Report 2021: HIV infection, diabetes mellitus, undernutrition, overcrowding, poverty, and indoor air pollution.

METHODS

We conducted a systematic literature search of PubMed, Embase, and Scopus databases to identify studies examining the association between climate variables and the risk factors for TB. Each study that satisfied the inclusion criteria was assessed for quality and ethics. Studies then underwent vote-counting and were categorised based on whether an association was found.

RESULTS

53 studies met inclusion criteria and were included in our review. Vote-counting revealed that two out of two studies found a positive association between the examined climate change proxy and HIV, nine out of twelve studies for diabetes, eight out of seventeen studies for undernutrition, four out of five studies for overcrowding, twelve out of fifteen studies for poverty and one out of three studies for indoor air pollution.

DISCUSSION

We found evidence supporting a positive association between climate change and each of the discussed risk factors for TB, excluding indoor air pollution. Our findings suggest that climate change is likely to affect the susceptibility of individuals to TB by increasing the prevalence of its underlying risk factors, particularly in developing countries. This is an evolving field of research that requires further attention in the scientific community.

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

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

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.