Dataset Information

Transmission of tuberculosis and predictors of large clusters within three years in an urban setting in Tokyo, Japan: a population-based molecular epidemiological study.

ABSTRACT:

Objective

Molecular epidemiology is a promising tool for understanding tuberculosis transmission dynamics but has not been sufficiently utilised in Asian countries including Japan. The aim of this study was to estimate the proportion of TB cases attributable to recent transmission and to identify risk factors of genotype clustering and the development of large clusters within 3 years in an urban setting in Japan.

Design and setting

Long-term cross-sectional observational study combining the characteristics of patients with culture-positive TB notified in Shinjuku City, Tokyo (2002-2013), with genotype data of Mycobacterium tuberculosis. PRIMARY OUTCOME MEASURE: Genotype clustering rate and association between genotype clustering status and explanatory variables.

Results

Among 1025 cases, 515 were localised within 113 genotype clusters. The overall clustering rate was 39.2%. Significantly higher rates were found in patients aged <40 years (adjusted odds ratio (aOR)=1.73, 95% CI 1.23 to 2.44), native Japanese individuals (aOR=3.90, 95% CI 2.27 to 6.72), full-time workers (aOR=1.63, 95% CI 1.17 to 2.27), part-time/daily workers (aOR=2.20, 95% CI 1.35 to 3.58), individuals receiving public assistance (aOR=1.81, 95% CI 1.15 to 2.84) and homeless people (aOR=1.63, 95% CI 1.02 to 2.62). A significant predictor of large genotype clusters within 3 years was a registration interval ≤2 months between the first two cases in a cluster.

Conclusion

Our results indicated that a large proportion of patients with culture-positive TB were involved in the recent TB transmission chain. Foreign-born persons still have a limited impact on transmission in the Japanese urban setting. Intensified public health interventions, including the active case finding, need to focus on individuals with socioeconomic risk factors that are significantly associated with tuberculosis transmission and clusters with shorter registration intervals between the first two cases.

SUBMITTER: Izumi K

PROVIDER: S-EPMC6527980 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Transmission of tuberculosis and predictors of large clusters within three years in an urban setting in Tokyo, Japan: a population-based molecular epidemiological study.

Izumi Kiyohiko K Murase Yoshiro Y Uchimura Kazuhiro K Kaebeta Aya A Ishihara Keiko K Kaguraoka Sumi S Takii Takemasa T Ohkado Akihiro A

BMJ open 20190509 5

<h4>Objective</h4>Molecular epidemiology is a promising tool for understanding tuberculosis transmission dynamics but has not been sufficiently utilised in Asian countries including Japan. The aim of this study was to estimate the proportion of TB cases attributable to recent transmission and to identify risk factors of genotype clustering and the development of large clusters within 3 years in an urban setting in Japan.<h4>Design and setting</h4>Long-term cross-sectional observational study com ...[more]

PMID: 31076478

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Project description:BackgroundCOVID-19 currently poses a global public health threat. Although Tokyo, Japan, is no exception to this, it was initially affected by only a small-level epidemic. Nevertheless, medical collapse nearly happened since no predictive methods were available to assess infection counts. A standard susceptible-infectious-removed (SIR) epidemiological model has been widely used, but its applicability is limited often to the early phase of an epidemic in the case of a large collective population. A full numerical simulation of the entire period from beginning until end would be helpful for understanding COVID-19 trends in (separate) counts of inpatient and infectious cases and can also aid the preparation of hospital beds and development of quarantine strategies.ObjectiveThis study aimed to develop an epidemiological model that considers the isolation period to simulate a comprehensive trend of the initial epidemic in Tokyo that yields separate counts of inpatient and infectious cases. It was also intended to induce important corollaries of governing equations (ie, effective reproductive number) and equations for the final count.MethodsTime-series data related to SARS-CoV-2 from February 28 to May 23, 2020, from Tokyo and antibody testing conducted by the Japanese government were adopted for this study. A novel epidemiological model based on a discrete delay differential equation (apparent time-lag model [ATLM]) was introduced. The model can predict trends in inpatient and infectious cases in the field. Various data such as daily new confirmed cases, cumulative infections, inpatients, and PCR (polymerase chain reaction) test positivity ratios were used to verify the model. This approach also derived an alternative formulation equivalent to the standard SIR model.ResultsIn a typical parameter setting, the present ATLM provided 20% less infectious cases in the field compared to the standard SIR model prediction owing to isolation. The basic reproductive number was inferred as 2.30 under the condition that the time lag T from infection to detection and isolation is 14 days. Based on this, an adequate vaccine ratio to avoid an outbreak was evaluated for 57% of the population. We assessed the date (May 23) that the government declared a rescission of the state of emergency. Taking into consideration the number of infectious cases in the field, a date of 1 week later (May 30) would have been most effective. Furthermore, simulation results with a shorter time lag of T=7 and a larger transmission rate of α=1.43α0 suggest that infections at large should reduce by half and inpatient numbers should be similar to those of the first wave of COVID-19.ConclusionsA novel mathematical model was proposed and examined using SARS-CoV-2 data for Tokyo. The simulation agreed with data from the beginning of the pandemic. Shortening the period from infection to hospitalization is effective against outbreaks without rigorous public health interventions and control.

Project description:ImportanceThere have been few studies on the heterogeneous interconnection of COVID-19 outbreaks occurring in different social settings using robust, surveillance epidemiological data.ObjectivesTo describe the characteristics of COVID-19 transmission within different social settings and to evaluate settings associated with onward transmission to other settings.Design, setting, and participantsThis is a case series study of laboratory-confirmed COVID-19 cases in Tokyo between January 23 and December 5, 2020, when vaccination was not yet implemented. Using epidemiological investigation data collected by public health centers, epidemiological links were identified and classified into 7 transmission settings: imported, nightlife, dining, workplace, household, health care, and other.Main outcomes and measuresThe number of cases per setting and the likelihood of generating onward transmissions were compared between different transmission settings.ResultsOf the 44 054 confirmed COVID-19 cases in this study, 25 241 (57.3%) were among male patients, and the median (IQR) age of patients was 36 (26-52) years. Transmission settings were identified in 13 122 cases, including 6768 household, 2733 health care, and 1174 nightlife cases. More than 6600 transmission settings were detected, and nightlife (72 of 380 [18.9%]; P < .001) and health care (119 [36.2%]; P < .001) settings were more likely to involve 5 or more cases than dining, workplace, household, and other settings. Nightlife cases appeared in the earlier phase of the epidemic, while household and health care cases appeared later. After adjustment for transmission setting, sex, age group, presence of symptoms, and wave, household and health care cases were less likely to generate onward transmission compared with nightlife cases (household: adjusted odds ratio, 0.03; 95% CI, 0.02-0.05; health care: adjusted odds ratio, 0.57; 95% CI, 0.41-0.79). Household settings were associated with intergenerational transmission, while nonhousehold settings mainly comprised transmission between the same age group. Among 30 932 cases without identified transmission settings, cases with a history of visiting nightlife establishments were more likely to generate onward transmission to nonhousehold settings (adjusted odds ratio, 5.30 [95% CI, 4.64-6.05]; P < .001) than those without such history.Conclusions and relevanceIn this case series study, COVID-19 cases identified in nightlife settings were associated with a higher likelihood of spreading COVID-19 than household and health care cases. Surveillance and interventions targeting nightlife settings should be prioritized to disrupt COVID-19 transmission, especially in the early stage of an epidemic.

Dataset Information

Transmission of tuberculosis and predictors of large clusters within three years in an urban setting in Tokyo, Japan: a population-based molecular epidemiological study.

Objective

Design and setting

Results

Conclusion

Publications

Transmission of tuberculosis and predictors of large clusters within three years in an urban setting in Tokyo, Japan: a population-based molecular epidemiological study.

Similar Datasets

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