Summary Background Since the coronavirus disease 2019 outbreak began in the Chinese city of Wuhan on Dec 31, 2019, 68 imported cases and 175 locally acquired infections have been reported in Singapore. We aimed to investigate options for early intervention in Singapore should local containment (eg, preventing disease spread through contact tracing efforts) be unsuccessful. Methods We adapted an influenza epidemic simulation model to estimate the likelihood of human-to-human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a simulated Singaporean population. Using this model, we estimated the cumulative number of SARS-CoV-2 infections at 80 days, after detection of 100 cases of community transmission, under three infectivity scenarios (basic reproduction number [R0] of 1·5, 2·0, or 2·5) and assuming 7·5% of infections are asymptomatic. We first ran the model assuming no intervention was in place (baseline scenario), and then assessed the effect of four intervention scenarios compared with a baseline scenario on the size and progression of the outbreak for each R0 value. These scenarios included isolation measures for infected individuals and quarantining of family members (hereafter referred to as quarantine); quarantine plus school closure; quarantine plus workplace distancing; and quarantine, school closure, and workplace distancing (hereafter referred to as the combined intervention). We also did sensitivity analyses by altering the asymptomatic fraction of infections (22·7%, 30·0%, 40·0%, and 50·0%) to compare outbreak sizes under the same control measures. Findings For the baseline scenario, when R0 was 1·5, the median cumulative number of infections at day 80 was 279 000 (IQR 245 000–320 000), corresponding to 7·4% (IQR 6·5–8·5) of the resident population of Singapore. The median number of infections increased with higher infectivity: 727 000 cases (670 000–776 000) when R0 was 2·0, corresponding to 19·3% (17·8–20·6) of the Singaporean population, and 1 207 000 cases (1 164 000–1 249 000) when R0 was 2·5, corresponding to 32% (30·9–33·1) of the Singaporean population. Compared with the baseline scenario, the combined intervention was the most effective, reducing the estimated median number of infections by 99·3% (IQR 92·6–99·9) when R0 was 1·5, by 93·0% (81·5–99·7) when R0 was 2·0, and by 78·2% (59·0 −94·4) when R0 was 2·5. Assuming increasing asymptomatic fractions up to 50·0%, up to 277 000 infections were estimated to occur at day 80 with the combined intervention relative to 1800 for the baseline at R0 of 1·5. Interpretation Implementing the combined intervention of quarantining infected individuals and their family members, workplace distancing, and school closure once community transmission has been detected could substantially reduce the number of SARS-CoV-2 infections. We therefore recommend immediate deployment of this strategy if local secondary transmission is confirmed within Singapore. However, quarantine and workplace distancing should be prioritised over school closure because at this early stage, symptomatic children have higher withdrawal rates from school than do symptomatic adults from work. At higher asymptomatic proportions, intervention effectiveness might be substantially reduced requiring the need for effective case management and treatments, and preventive measures such as vaccines. Funding Singapore Ministry of Health, Singapore Population Health Improvement Centre.

Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study

The COVID-19 outbreak spread like a forest fire in the first quarter of 2020. Until September, more than 26 million people were affected by this epidemic. It has been 9 months since the first case was seen. However, a curative treatment method or vaccine has not been developed yet. Today, the only approach that can prevent the outbreak is classical epidemic control approaches such as hygiene, case isolation, contact tracing and quarantine. Contact tracing aims to reduce the spread of the epidemic by trying to analyze the potential transmission routes of the infection at the individual level. In addition, it will be possible to prevent official measures such as the curfew taken to prevent the epidemic from spreading. However, when considering ways of communication between people, the epidemic knows no boundaries. Mobile applications and artificial intelligence can be successful in analyzing this contact chain. Even if protecting human life is the highest degree moral duty, these methods contain many ethical problems. The most violated ethical values because of these practices are privacy, confidentiality of information, civil freedom and autonomy. In this study, we will try to analyze the ethical problems that arise with contact tracing mobile applications in the context of COVID-19. © 2021, DOC Design and Informatics Co. Ltd.. All rights reserved.

Contact tracing in the context of covid-19: Ethical issues and assessment

SARS-CoV-2 prevalence associated to low socioeconomic status and overcrowding in an LMIC megacity: A population-based seroepidemiological survey in Lima, Peru

Cost-effectiveness of the COVID-19 test, trace and isolate program in Colombia

Summary Background During the COVID-19 pandemic, Test-Trace-Isolate (TTI) programs have been recommended as a risk mitigation strategy. However, many governments have hesitated to implement them due to their costs. This study aims to estimate the cost-effectiveness of implementing a national TTI program to reduce the number of severe and fatal cases of COVID-19 in Colombia. Methods We developed a Markov simulation model of COVID-19 infection combined with a Susceptible-Infected-Recovered structure. We estimated the incremental cost-effectiveness of a comprehensive TTI strategy compared to no intervention over a one-year horizon, from both the health system and the societal perspective. Hospitalization and mortality rates were retrieved from Colombian surveillance data. We included program costs of TTI intervention, health services utilization, PCR diagnosis test, productivity loss, and government social program costs. We used the number of deaths and quality-adjusted life years (QALYs) as health outcomes. Sensitivity analyses were performed. Findings Compared with no intervention, the TTI strategy reduces COVID-19 mortality by 67%. In addition, the program saves an average of $1,045 and $850 per case when observed from the social and the health system perspective, respectively. These savings are equivalent to two times the current health expenditures in Colombia per year. Interpretation The TTI program is a highly cost-effective public health intervention to reduce the burden of COVID-19 in Colombia. TTI programs depend on their successful and speedy implementation. Funding This study was supported by the Colombian Ministry of Health through award number PUJ-04519-20 received by EPQ AVO and SDS declined to receive any funding support for this study. The contents are the responsibility of all the individual authors.

Cost-Effectiveness of the COVID-19 Test, Trace and Isolate Program in Colombia.

BACKGROUND: Contact tracing is a crucial part of the public health surveillance toolkit. However, it is labor-intensive and costly to carry it out. Some countries have faced challenges implementing contact tracing, and no impact evaluations using empirical data have assessed its impact on COVID-19 mortality. This study assesses the impact of contact tracing in a middle-income country, providing data to support the expansion and optimization of contact tracing strategies to improve infection control. METHODS: We obtained publicly available data on all confirmed COVID-19 cases in Colombia between March 2 and June 16, 2020. (N = 54,931 cases over 135 days of observation). As suggested by WHO guidelines, we proxied contact tracing performance as the proportion of cases identified through contact tracing out of all cases identified. We calculated the daily proportion of cases identified through contact tracing across 37 geographical units (32 departments and five districts). Further, we used a sequential log-log fixed-effects model to estimate the 21-days, 28-days, 42-days, and 56-days lagged impact of the proportion of cases identified through contact tracing on daily COVID-19 mortality. Both the proportion of cases identified through contact tracing and the daily number of COVID-19 deaths are smoothed using 7-day moving averages. Models control for the prevalence of active cases, second-degree polynomials, and mobility indices. Robustness checks to include supply-side variables were performed. RESULTS: We found that a 10 percent increase in the proportion of cases identified through contact tracing is related to COVID-19 mortality reductions between 0.8% and 3.4%. Our models explain between 47%-70% of the variance in mortality. Results are robust to changes of specification and inclusion of supply-side variables. CONCLUSION: Contact tracing is instrumental in containing infectious diseases. Its prioritization as a surveillance strategy will substantially impact reducing deaths while minimizing the impact on the fragile economic systems of lower and middle-income countries. This study provides lessons for other LMIC.

/pdf/impact-of-contact-tracing-on-covid-19-mortality-an-impact-2hkgju3ynu.pdf

Impact of contact tracing on COVID-19 mortality: An impact evaluation using surveillance data from Colombia.

Background Contact tracing is a key part of the public health surveillance toolkit. However, it is labor intensive and costly to carry it out. Some countries have faced challenges implementing contact tracing, and no impact evaluations to our knowledge have assessed its impact on COVID-19 mortality. This study assesses the impact of contact tracing in a middle-income country and provides data to support the expansion of contact tracing strategies with the aim of improving infection control. Methods We obtained publicly available data on all confirmed COVID-19 cases in Colombia between March 2 and June 16, 2020. (N=54,931 cases over 135 days of observation). We proxied contact tracing performance as the proportion of cases identified through contact tracing out of all cases identified, as suggested by WHO guidelines. We calculated the daily proportion of cases identified through contact tracing across 37 geographical units (32 departments and five districts). Further, we used a sequential log-log fixed-effects model to estimate the 21-days, 28-days, 42-days and 56-days lagged impact of the proportion of cases identified through contact tracing on the daily number of COVID-19 deaths. Both the proportion of cases identified through contact tracing and the daily number of COVID-19 deaths are smoothed using 7-day moving averages. Models control for prevalence of active cases, second-degree polynomials, and mobility indices. Robustness checks to include supply-side variables were performed. Results We found that a 10 percent increase in the proportion of cases identified through contact tracing is related to COVID-19 mortality reductions between 0.8% and 3.4%. Our models explain between 47%-70% of the variance in mortality. Results are robust to changes of specification and inclusion of supply-side variables. Conclusion Contact tracing is instrumental to contain infectious diseases and its prioritization as a surveillance strategy will have a substantial impact on reducing deaths while minimizing the impact on the fragile economic systems of lower and middle-income countries. This study provides lessons for other LMIC.

https://medrxiv.org/content/10.1101/2020.08.14.20158535v1.full.pdf

Silvana Zapata Bedoya

Papers

Impact of contact tracing on COVID-19 mortality: An impact evaluation using surveillance data from Colombia.

Impact of contact tracing on COVID-19 mortality: An impact evaluation using surveillance data from Colombia