Factors Influencing the Effectiveness of Adopting Electronic Medical Record-Based Reporting Systems for Notifiable Disease Surveillance: A Quantitative Analysis.

The coronavirus disease 2019 (COVID-19) pandemic has led to greater attention being given to infectious disease surveillance systems and their notification functionalities. Although numerous studies have explored the benefits of integrating functionalities with electronic medical record (EMR) systems, empirical studies on the topic are rare. The current study assessed which factors influence the effectiveness of EMR-based reporting systems (EMR-RSs) for notifiable disease surveillance. This study interviewed staff from hospitals with a coverage that represented 51.39% of the notifiable disease reporting volume in Taiwan. Exact logistic regression was employed to determine which factors influenced the effectiveness of Taiwan's EMR-RS. The results revealed that the influential factors included hospitals' early participation in the EMR-RS project, frequent consultation with the information technology (IT) provider of the Taiwan Centers for Disease Control (TWCDC), and retrieval of data from at least one internal database. They also revealed that using an EMR-RS resulted in more timely, accurate, and convenient reporting in hospitals. In addition, developing by an internal IT unit instead of outsourcing EMR-RS development led to more accurate and convenient reporting. Automatically loading the required data enhanced the convenience, and designing input fields that may be unavailable in current databases to enable physicians to add data to legacy databases also boosted effectiveness of the reporting system.

Early Prompt Response to COVID-19 in Taiwan: Comprehensive surveillance, decisive border control, and information technology support.

Since the COVID-19 outbreak was detected in Wuhan in December 2019 by the event-based surveillance of Taiwan Centers for Disease Control, Taiwan has been aligning risk management to policy planning with the assistance of comprehensive surveillance and regular rapid risk assessments. Taiwan Central Epidemic Command Center (CECC) promptly initiated stepwise border control for major cities and provinces in China, European and American countries, and eventually expanded it to the whole world in March 2020. With stringent quarantine measures, the early response not only successfully blocked the first wave of imported cases, but also slowed down subsequent large local outbreaks. Digital technologies including digital fencing and government database linkage were adopted to facilitate the application of public health interventions and data collection. The experience of Taiwan's prompt and comprehensive response at the early stage may contribute to the preparedness for the next disease X outbreak.

The secular trend of enterovirus A71 after the implementation of preventive measures in Taiwan.

BACKGROUND: Enterovirus A71 (EV A71) is one of the most important enteroviruses related to morbidity and mortality in children worldwide. This study aimed to analyse the secular trend of EV A71 in Taiwan from 1998 to 2020 and to evaluate the effectiveness of infection control measures. METHODS: We collected the epidemiological data of EV A71 from disease surveillance systems in Taiwan. We analysed the association between the secular trend of EV A71 and preventive measures such as hand washing, case isolation, and suspension of classes. RESULTS: The incidence of enterovirus infections with severe complications (EVSC) decreased from 16.25 per 100,000 children under six in 1998 to less than 9.73 per 100,000 children under six after 2012 (P = 0.0022). The mortality rate also decreased significantly, from 3.52 per 100,000 children under six in 1998 to 0 per 100,000 children under six in 2020 (P < 0.0001). The numbers of EVSC and fatalities were significantly higher in the years when EV A71 accounted for more than 10% of the annual predominant serotypes (p < 0.05). After the implementation of many non-pharmaceutical interventions in 2012, the incidence of EVSC and mortality rate decreased significantly (p < 0.001). CONCLUSIONS: After implementing active enterovirus surveillance and preventive measures, we found that the incidence of EVSC and fatalities due to EV A71 in Taiwan decreased significantly from 1998 to 2020. Continuous surveillance and strengthened infection control policies are still needed in the future.

A comprehensive evaluation of COVID-19 policies and outcomes in 50 countries and territories.

The COVID-19 pandemic struck the world unguarded, some places outperformed others in COVID-19 containment. This longitudinal study considered a comparative evaluation of COVID-19 containment across 50 distinctly governed regions between March 2020 and November 2021. Our analysis distinguishes between a pre-vaccine phase (March-November 2020) and a vaccinating phase (December 2020-November 2021). In the first phase, we develop an indicator, termed lockdown efficiency (LE), to estimate the efficacy of measures against monthly case numbers. Nine other indicators were considered, including vaccine-related indicators in the second phase. Linear mixed models are used to explore the relationship between each government policy & hygiene education (GP&HE) indicator and each vital health & socioeconomic (VH&SE) measure. Our ranking shows that surveyed countries in Oceania and Asian outperformed countries in other regions for pandemic containment prior to vaccine development. Their success appears to be associated with non-pharmaceutical interventions, acting early, and adjusting policies as needed. After vaccines have been distributed, maintaining non-pharmacological intervention is the best way to achieve protection from variant viral strains, breakthrough infections, waning vaccine efficacy, and vaccine hesitancy limiting of herd immunity. The findings of the study provide insights into the effectiveness of emerging infectious disease containment policies worldwide.

Comparison of Estimated Effectiveness of Case-Based and Population-Based Interventions on COVID-19 Containment in Taiwan.

Importance: Taiwan is one of the few countries with initial success in COVID-19 control without strict lockdown or school closure. The reasons remain to be fully elucidated. Objective: To compare and evaluate the effectiveness of case-based (including contact tracing and quarantine) and population-based (including social distancing and facial masking) interventions for COVID-19 in Taiwan. Design, Setting, and Participants: This comparative effectiveness study used a stochastic branching process model using COVID-19 epidemic data from Taiwan, an island nation of 23.6 million people, with no locally acquired cases of COVID-19 reported for 253 days between April and December 2020. Main Outcomes and Measures: Effective reproduction number of COVID-19 cases (the number of secondary cases generated by 1 primary case) and the probability of outbreak extinction (0 new cases within 20 generations). For model development and calibration, an estimation of the incubation period (interval from exposure to symptom onset), serial interval (time between symptom onset in an infector-infectee pair), and the statistical distribution of the number of any subsequent infections generated by 1 primary case was calculated. Results: This study analyzed data from 158 confirmed COVID-19 cases (median age, 45 years; interquartile range, 25-55 years; 84 men [53%]). An estimated 55% (95% credible interval [CrI], 41%-68%) of transmission events occurred during the presymptomatic stage. In our estimated analysis, case detection, contact tracing, and 14-day quarantine of close contacts (regardless of symptoms) was estimated to decrease the reproduction number from the counterfactual value of 2.50 to 1.53 (95% CrI, 1.50-1.57), which would not be sufficient for epidemic control, which requires a value of less than 1. In our estimated analysis, voluntary population-based interventions, if used alone, were estimated to have reduced the reproduction number to 1.30 (95% CrI, 1.03-1.58). Combined case-based and population-based interventions were estimated to reduce the reproduction number to below unity (0.85; 95% CrI, 0.78-0.89). Results were similar for additional analyses with influenza data and sensitivity analyses. Conclusions and Relevance: In this comparative effectiveness research study, the combination of case-based and population-based interventions (with wide adherence) may explain the success of COVID-19 control in Taiwan in 2020. Either category of interventions alone would have been insufficient, even in a country with an effective public health system and comprehensive contact tracing program. Mitigating the COVID-19 pandemic requires the collaborative effort of public health professionals and the general public.

Risk assessment for COVID-19 pandemic in Taiwan.

BACKGROUND AND OBJECTIVES: Event-based surveillance and rapid risk assessment for acute public health events are essential in emerging infectious disease control. Since detecting the unusual signal in Wuhan in December 2019, Taiwan has been aligning risk management to policy planning via conducting regular risk assessments to combat the coronavirus disease 2019 (COVID-19). This article aims to provide some insights into Taiwan's experiences and corresponding actions for the outbreak. RESULTS: The COVID-19 risk level in Taiwan was raised to "moderate-to-high" in mid-January 2020 when neighboring countries had reported cases and the human-to-human transmission became obvious. The risk level became "high" on 24 January due to China's escalating epidemic situation and imposed a lockdown in Wuhan. We learned that the commander recognized the importance of risk assessments and considered advice from the experts was crucial in making the correct decision at the early stage of the crisis. CONCLUSIONS: Given the surge of COVID-19 cases globally, understanding the evidence-driven mobilizations via detailed risk assessments in Taiwan may be an example worth considering for other countries. We believe that strengthening a global epidemic intelligence network and sharing information in a timely and transparent manner are essential for confronting new challenges of COVID-19 and other emerging infectious diseases.

Taiwan's COVID-19 response: Timely case detection and quarantine, January to June 2020.

The coronavirus disease 2019 (COVID-19) pandemic has become severe threats to economic, societal, and healthcare systems. To analyze the epidemiological characteristics of the COVID-19 outbreak in Taiwan and evaluate the key interventions, we conducted a retrospective cohort study during January 17-June 30, 2020. As of June 30, the COVID-19 outbreak, including 447 laboratory-confirmed cases, was eliminated by mixed approaches: border control, enhanced surveillance, case detection with contact tracing, quarantine, and population-based interventions like face mask use. The improvement of median time from disease onset to notification (5 days [range -3 to 27] before March 1 to 1 day [range -8 to 22] after March 1) suggested the timeliness and comprehensiveness of surveillance and contact tracing. Travel restrictions with quarantine, resulting in fewer clusters, were also complementary to minimize disease spread. Under combined interventions, Taiwan successfully contained the COVID-19 spread within the country and minimized its impact on the society.

Contact tracing with digital assistance in Taiwan's COVID-19 outbreak response.

AIM: Comprehensive case investigation and contact tracing are crucial to prevent community spread of COVID-19. We demonstrated a utility of using traditional contact tracing measures supplemented with symptom tracking and contact management system to assist public health workers with high efficiency. METHODS: A centralized contact tracing system was developed to support data linkage, cross-jurisdictional coordination, and follow-up of contacts' health status. We illustrated the process of how digital tools support contact tracing and management of COVID-19 cases and measured the timeliness from case detection to contact monitoring to evaluate system performance. RESULTS: Among the 8051 close contacts of the 487 confirmed cases (16.5 close contacts/case, 95% CI [13.9-19.1]), the median elapsed time from last exposure to quarantine was three days (IQR 1-5). By implementing the approach of self-reporting using automatic text-messages and web-app, the percentage of health status updates from self-reporting increased from 22.5% to 61.5%. The high proportion of secondary cases detected via contact tracing (88%) might reduce the R0 to under one and minimize the impact of local transmission in the community. CONCLUSION: Comprehensive contact tracing and management with complementary technology would still be a pillar of strategies for containing outbreaks during de-escalation or early in the next wave of COVID-19 pandemic.

Applying Machine Learning Models with An Ensemble Approach for Accurate Real-Time Influenza Forecasting in Taiwan: Development and Validation Study.

BACKGROUND: Changeful seasonal influenza activity in subtropical areas such as Taiwan causes problems in epidemic preparedness. The Taiwan Centers for Disease Control has maintained real-time national influenza surveillance systems since 2004. Except for timely monitoring, epidemic forecasting using the national influenza surveillance data can provide pivotal information for public health response. OBJECTIVE: We aimed to develop predictive models using machine learning to provide real-time influenza-like illness forecasts. METHODS: Using surveillance data of influenza-like illness visits from emergency departments (from the Real-Time Outbreak and Disease Surveillance System), outpatient departments (from the National Health Insurance database), and the records of patients with severe influenza with complications (from the National Notifiable Disease Surveillance System), we developed 4 machine learning models (autoregressive integrated moving average, random forest, support vector regression, and extreme gradient boosting) to produce weekly influenza-like illness predictions for a given week and 3 subsequent weeks. We established a framework of the machine learning models and used an ensemble approach called stacking to integrate these predictions. We trained the models using historical data from 2008-2014. We evaluated their predictive ability during 2015-2017 for each of the 4-week time periods using Pearson correlation, mean absolute percentage error (MAPE), and hit rate of trend prediction. A dashboard website was built to visualize the forecasts, and the results of real-world implementation of this forecasting framework in 2018 were evaluated using the same metrics. RESULTS: All models could accurately predict the timing and magnitudes of the seasonal peaks in the then-current week (nowcast) (ρ=0.802-0.965; MAPE: 5.2%-9.2%; hit rate: 0.577-0.756), 1-week (ρ=0.803-0.918; MAPE: 8.3%-11.8%; hit rate: 0.643-0.747), 2-week (ρ=0.783-0.867; MAPE: 10.1%-15.3%; hit rate: 0.669-0.734), and 3-week forecasts (ρ=0.676-0.801; MAPE: 12.0%-18.9%; hit rate: 0.643-0.786), especially the ensemble model. In real-world implementation in 2018, the forecasting performance was still accurate in nowcasts (ρ=0.875-0.969; MAPE: 5.3%-8.0%; hit rate: 0.582-0.782) and remained satisfactory in 3-week forecasts (ρ=0.721-0.908; MAPE: 7.6%-13.5%; hit rate: 0.596-0.904). CONCLUSIONS: This machine learning and ensemble approach can make accurate, real-time influenza-like illness forecasts for a 4-week period, and thus, facilitate decision making.

Contact Tracing Assessment of COVID-19 Transmission Dynamics in Taiwan and Risk at Different Exposure Periods Before and After Symptom Onset.

Importance: The dynamics of coronavirus disease 2019 (COVID-19) transmissibility are yet to be fully understood. Better understanding of the transmission dynamics is important for the development and evaluation of effective control policies. Objective: To delineate the transmission dynamics of COVID-19 and evaluate the transmission risk at different exposure window periods before and after symptom onset. Design, Setting, and Participants: This prospective case-ascertained study in Taiwan included laboratory-confirmed cases of COVID-19 and their contacts. The study period was from January 15 to March 18, 2020. All close contacts were quarantined at home for 14 days after their last exposure to the index case. During the quarantine period, any relevant symptoms (fever, cough, or other respiratory symptoms) of contacts triggered a COVID-19 test. The final follow-up date was April 2, 2020. Main Outcomes and Measures: Secondary clinical attack rate (considering symptomatic cases only) for different exposure time windows of the index cases and for different exposure settings (such as household, family, and health care). Results: We enrolled 100 confirmed patients, with a median age of 44 years (range, 11-88 years), including 44 men and 56 women. Among their 2761 close contacts, there were 22 paired index-secondary cases. The overall secondary clinical attack rate was 0.7% (95% CI, 0.4%-1.0%). The attack rate was higher among the 1818 contacts whose exposure to index cases started within 5 days of symptom onset (1.0% [95% CI, 0.6%-1.6%]) compared with those who were exposed later (0 cases from 852 contacts; 95% CI, 0%-0.4%). The 299 contacts with exclusive presymptomatic exposures were also at risk (attack rate, 0.7% [95% CI, 0.2%-2.4%]). The attack rate was higher among household (4.6% [95% CI, 2.3%-9.3%]) and nonhousehold (5.3% [95% CI, 2.1%-12.8%]) family contacts than that in health care or other settings. The attack rates were higher among those aged 40 to 59 years (1.1% [95% CI, 0.6%-2.1%]) and those aged 60 years and older (0.9% [95% CI, 0.3%-2.6%]). Conclusions and Relevance: In this study, high transmissibility of COVID-19 before and immediately after symptom onset suggests that finding and isolating symptomatic patients alone may not suffice to contain the epidemic, and more generalized measures may be required, such as social distancing.

Assessment of Expert-Level Automated Detection of Plasmodium falciparum in Digitized Thin Blood Smear Images.

Importance: Decades of effort have been devoted to establishing an automated microscopic diagnosis of malaria, but there are challenges in achieving expert-level performance in real-world clinical settings because publicly available annotated data for benchmark and validation are required. Objective: To assess an expert-level malaria detection algorithm using a publicly available benchmark image data set. Design, Setting, and Participants: In this diagnostic study, clinically validated malaria image data sets, the Taiwan Images for Malaria Eradication (TIME), were created by digitizing thin blood smears acquired from patients with malaria selected from the biobank of the Taiwan Centers for Disease Control from January 1, 2003, to December 31, 2018. These smear images were annotated by 4 clinical laboratory scientists who worked in medical centers in Taiwan and trained for malaria microscopic diagnosis at the national reference laboratory of the Taiwan Centers for Disease Control. With TIME, a convolutional neural network-based object detection algorithm was developed for identification of malaria-infected red blood cells. A diagnostic challenge using another independent data set within TIME was performed to compare the algorithm performance against that of human experts as clinical validation. Main Outcomes and Measures: Performance on detecting Plasmodium falciparum-infected blood cells was measured by average precision, and performance on detecting P falciparum infection at the image level was measured using sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: The TIME data sets contained 8145 images of 36 blood smears from patients with suspected malaria (30 P falciparum-positive and 6 P falciparum-negative smears) that had reliable annotations. For clinical validation, the average precision was 0.885 for detecting P falciparum-infected blood cells and 0.838 for ring form. For detecting P falciparum infection on blood smear images, the algorithm had expert-level performance (sensitivity, 0.995; specificity, 0.900; AUC, 0.997 [95% CI, 0.993-0.999]), especially in detecting ring form (sensitivity, 0.968; specificity, 0.960; AUC, 0.995 [95% CI, 0.990-0.998]) compared with experienced microscopists (mean sensitivity, 0.995 [95% CI, 0.993-0.998]; mean specificity, 0.955 [95% CI, 0.885-1.000]). Conclusions and Relevance: The findings suggest that a clinically validated expert-level malaria detection algorithm can be developed by using reliable data sets.

Enterovirus 71 seroepidemiology in Taiwan in 2017 and comparison of those rates in 1997, 1999 and 2007.

BACKGROUND: During recent 20 years, enterovirus 71 (EV71) has emerged as a major concern among children, particularly in the Asia-Pacific region. To understand current EV71 serostatus, to find risk factors associated with EV71 infection and to establish future EV71 vaccine policy, we performed a seroepidemiology study in Taiwan in 2017. METHODS: After informed consent was obtained, we enrolled preschool children, 6-15-year-old students, 16-50-year-old people. They received a questionnaire and a blood sample was collected to measure the EV71 neutralization antibody. RESULTS: Altogether, 920 subjects were enrolled with a male-to-female ratio of 1.03. The EV71 seropositive rate was 10% (8/82) in infants, 4% (6/153) in 1-year-old children, 8% (7/83) in 2-year-old children, 8% (13/156) in 3-5-year-old children, 31% (38/122) in 6-11-year-old primary school students, 45% (54/121) in 12-15-year-old high school students and 75% (152/203) in 16-50-year-old people. Risk factors associated with EV71 seropositivity in preschool children were female gender, having siblings, more siblings, and contact with herpangina or hand-foot-and-mouth disease. The risk factor with EV71 seropositivity in 16-50-year-old people was having children in their families in addition to older age (p<0.001). Compared with the rates in 1997, 1999 and 2007, the rates in children were significantly lower in 2017. CONCLUSION: EV71 seropositive rates were very low, at 4% to 10%, in preschool children and not high, at 31%, in primary school students. Preschool children are highly susceptible and need EV71 vaccine most.

[Research progress on chemical constituents and biological activities from Turpinia species].

Turpinia species have been used as local Chinese medicines. It has been widely concerned about their antibacterial and anti-inflammatory effects. Modern studies showed that the chemical constituents of Turpina species include flavonoids, triterpenoids, megastigans and phenoli acids. Its pharmacological research mainly focused on antibacterial, anti-inflammatory, antioxidant, analgesic, and immuneregulation effect. In this paper, the chemical compositions and pharmacological activities of Turpinia species were summarized, in order to provide scientific basis for the further development and utilization of Turpinia species.

[Sesquiterpenes with anti-metastasis breast cancer activity from Chloranthus henryi].

To study sesquiterpenes with anti-metastasis breast cancer activity from Chloranthus henryi, ten sesquiterpenes ,zedoarofuran (1), chlorajapolide D (2), 4ß, 8ß-dihydroxy-5α(H)-eudesm-7(11)-en-8, 12-olide (3), curcolonol (4), lasianthuslactone A (5), chlomultin C (6), (1E,4Z)-8-hydroxy-6-oxogermacra-1(10), 4, 7(11) -trieno-12, 8-lactone (7), shizukanolide E (8) , shizukanolide F (9) , 9α-hydroxycurcolonol (10), and five bis-sesquiterpenes, shizukaol B (11), shizukaol C (12) , cycloshizukaol A (13) , sarcandrolide B (14) , henriol A(15), were isolated by using different kinds of column chromatography methods from the ethyl acetate part of Ch.henryi and their structures were identified based on spectroscopic methods. Compounds 2, 8, 9, and 10 were obtained from the genus Chloranthus for the first time. Compounds 2, 5, 8-10, 12,and 14 were obtained from this plant for the first time. Some isolated compounds were subjected to evaluate the anti-metastasis breast cancer activity by using pharmacological methods, and only compounds 4, 11, and 12 were potent active.

Real-Time Surveillance of Infectious Diseases: Taiwan's Experience.

Integration of multiple surveillance systems advances early warning and supports better decision making during infectious disease events. Taiwan has a comprehensive network of laboratory, epidemiologic, and early warning surveillance systems with nationwide representation. Hospitals and clinical laboratories have deployed automatic reporting mechanisms since 2014 and have effectively improved timeliness of infectious disease and laboratory data reporting. In June 2016, the capacity of real-time surveillance in Taiwan was externally assessed and was found to have a demonstrated and sustainable capability. We describe Taiwan's disease surveillance system and use surveillance efforts for influenza and Zika virus as examples of surveillance capability. Timely and integrated influenza information showed a higher level and extended pattern of influenza activity during the 2015-16 season, which ensured prompt information dissemination and the coordination of response operations. Taiwan also has well-developed disease detection systems and was the first country to report imported cases of Zika virus from Miami Beach and Singapore. This illustrates a high level of awareness and willingness among health workers to report emerging infectious diseases, and highlights the robust and sensitive nature of Taiwan's surveillance system. These 2 examples demonstrate the flexibility of the surveillance systems in Taiwan to adapt to emerging infectious diseases and major communicable diseases. Through participation in the GHSA, Taiwan can more actively collaborate with national counterparts and use its expertise to strengthen global and regional surveillance capacity in the Asia Pacific and in Southeast Asia, in order to advance a world safe and secure from infectious disease.

Toward Automatic Reporting of Infectious Diseases.

Accurate, complete, and timely disease surveillance data are vital for disease control. We report a national scale effort to automatically extract information from electronic medical records as well as electronic laboratory systems. The extracted information is then transferred to the centers of disease control after a proper confirmation process. The coverage rates of the automated reporting systems are over 50%. Not only is the workload of surveillance greatly reduced, but also reporting is completed in near real-time. From our experiences, a system sustainable strategy, well-defined working plan, and multifaceted team coordination work effectively. Knowledge management reduces the cost to maintain the system. Training courses with hands-on practice and reference documents are useful for LOINC adoption.

Disease burden of enterovirus infection in Taiwan: Implications for vaccination policy.

OBJECTIVES: This study aimed to assess the disease burden and economic impacts of human nonpolio enteroviruses (NPEV) and enterovirus A71 (EV-A71) infection in Taiwan. MATERIALS AND METHODS: We included children under five years old (n=983,127-1,118,649) with ICD-9-CM codes 0740 (herpangina) or 0743 (hand-foot-and-mouth disease) from the 2006 to 2010 National Health Insurance Database. Severity of enterovirus infection was assessed from outpatient/emergency visits, hospitalization (with/without intensive care unit [ICU] admission), infection with severe complications, and death. We estimated medical costs and indirect costs from the societal perspective. RESULTS: The annual rates of NPEV events for children under five years old ranged from 13.9% to 38.4%, of which 5.1-8.8% were hospitalized. EV-A71 accounted for 7.8% of all NPEV medical costs, but 79.1% of NPEV ICU costs. Travel costs and productivity loss of caregivers were $37.1 (range: $24.5-$64.7) million per year. These costs were not higher in the EV-A71 dominant year ($34.4 million) compared with those in the other years. Productivity losses resulting from premature mortality by NPEV infection were $0.8 (range: $0.0-$2.9) million per year, of which 96.3% were caused by EV-A71. CONCLUSIONS: Diseases associated with NPEV other than EV-A71 were responsible for most of the medical expenses. In addition, caregiver productivity loss by high rates of NPEV infection impacted the society much more than medical costs. A multi-valent vaccine that includes EV-A71 and other serotypes, for example coxsackievirus A16, may be beneficial to the health of children in Taiwan.

Ambient air pollution and risk of tuberculosis: a cohort study.

OBJECTIVES: Several respirable hazards, including smoking and indoor air pollution from biomass, were suggested to increase the risk of tuberculosis. Few studies have been conducted on ambient air pollution and tuberculosis. We investigated the association between exposure to ambient air pollution and incidence of active tuberculosis. METHODS: We conducted a cohort study using 106,678 participants of a community-based screening service in Taiwan, 2005-2012. We estimated individual exposure to air pollution using data from the nearest air quality monitoring station and the road intensity within a 500 m buffer zone. The incidence of tuberculosis was ascertained from the national tuberculosis registry. RESULTS: After a median follow-up of 6.7 years, 418 cases of tuberculosis occurred. Exposure to fine particulate matter (PM2.5) was associated with increased risk of active tuberculosis (adjusted HR: 1.39/10 µg/m3 (95% CI 0.95 to 2.03)). In addition, traffic-related air pollution including nitrogen dioxide (adjusted HR: 1.33/10 ppb; 95% CI 1.04 to 1.70), nitrogen oxides (adjusted HR: 1.21/10 ppb; 95% CI 1.04 to 1.41) and carbon monoxide (adjusted HR: 1.89/ppm; 95% CI 0.78 to 4.58) was associated with tuberculosis risk. There was a non-significant trend between the length of major roads in the neighbourhood and culture-confirmed tuberculosis (adjusted HR: 1.04/km; 95% CI 0.995 to 1.09). CONCLUSIONS: Our study revealed a possible link between ambient air pollution and risk of active tuberculosis. Since people from developing countries continue to be exposed to high levels of ambient air pollution and to experience high rates of tuberculosis, the impact of worsening air pollution on global tuberculosis control warrants further investigation.