Infectious Disease Surveillance and Control for Pandemic Prevention, Preparedness, and Response

Abstract

Infectious Disease Surveillance and Control for Pandemic Prevention, Preparedness, and Response

Chapter Two: Modeling the Effects of Routine Screening for Accidental Lab-Acquired Infections on the Risk of Potential Pandemic Pathogen Escape from High-Biosafety Research Facilities

Justification: There is increasing concern in the scientific community about the risk that an accidental Lab-Acquired Infection (LAI) in a BSL-4 or BSL-3 laboratory could lead to the release of a Potential Pandemic Pathogen (PPP) into the community. Objectives: We evaluated the utility of routine testing of lab workers for accidental infection coupled with isolation of infected lab workers to reduce the risk of a catastrophic accidental outbreak of a PPP. Methods: We constructed a stochastic network infectious disease model to simulate how the probability of an outbreak of a pathogen resembling wild-type SARS-COV-2 following an initial accidental lab-acquired infection would be influenced by a variety of test-and-isolate interventions. We manipulated key parameters across simulations including test frequency, test sensitivity, and length of average delay from positive test to isolation. Main Results: Simulation results indicated that under a wide range of plausible assumptions, even relatively infrequent routine testing could substantially reduce the risk of LAIs sparking outbreaks with a PPP, and that the largest risk reductions could be achieved with more frequent testing. Under moderately optimistic assumptions of peak test sensitivity of 80% and an average delay of one day from taking a positive test to implementation of effective isolation, the risk of an outbreak of 50 or more infections could be reduced by 52% with one test per week, 62% with two tests per week, and 71% with five tests per week. Under pessimistic assumptions of peak test sensitivity of 50% and an average delay of two days from taking a positive test to implementation of effective isolation, the risk of an outbreak of 50 or more infections could be reduced by 29% with one test per week, 43% with two tests per week, and 55% with five tests per week. Simulation results also indicated that as test sensitivity increased, the probability of an outbreak occurring decreased. Additionally, as the length of isolation delays increased, so did the probability of an outbreak. The impact of increasing test frequency and sensitivity on the probability of an outbreak were both reduced as isolation delays increased. The impact of increasing isolation delays on the probability of outbreaks was also magnified by increases in test frequency and test sensitivity. Conclusions: Routine testing for LAIs in high-biosafety research facilities could substantially reduce the risk of an outbreak of a potential pandemic pathogen similar to wild-type SARS-COV-2.

Chapter Three: Epidemiologic Moderators of the Effectiveness of Routine Screening for LAIs in High-Biosafety Environments

Justification: Accidental lab-acquired infections (LAIs) with potential pandemic pathogens (PPPs) in high-biosafety research facilities risk causing a pandemic. Routine testing of lab workers for LAIs coupled with isolation of infected workers could reduce the risk, but the impact of such an intervention may depend on pathogens’ epidemiological characteristics. Objective: This study aims to understand how the epidemiological characteristics of PPPs moderate the efficacy of a routine testing and isolation intervention in preventing larger outbreaks after an LAI. Methods: We employed a discrete-time stochastic network infectious disease model to run 625,000 epidemic simulations encompassing 625 unique combinations of five parameters of interest: test frequency, pathogen transmissibility, the self-isolation rate for symptomatic cases, the percentage of cases that are asymptomatic, and the percentage of infectious time that is spent in the pre-symptomatic state among those who show symptoms. To summarize the Monte Carlo simulations, we paired visual analysis with logistic regression for formal hypothesis testing, with an emphasis on the interaction terms that capture the moderating effect of epidemiological parameters on the impact of test frequency. Main Results: There were four main findings. First, the relative reductions in risk of outbreak that were caused by increased test frequency were inversely correlated with pathogen transmissibility. Second, the effect of test frequency was magnified at higher asymptomatic shares when the symptomatic self-isolation rate was high, but minimally when the self-isolation rate is low. Third, the direction of how the symptomatic self-isolation rate moderated the effect of increased test frequency depended on the asymptomatic share. Fourth, as the pre-symptomatic share of infectious time increased, the effect of test frequency on the probability of an outbreak was strongly magnified largely independent of symptomatic self-isolation rates. Conclusions: Routine testing and isolation could significantly mitigate the risk of catastrophic PPP escapes, with the intervention's success varying based on pathogen characteristics. High shares of asymptomatic and pre-symptomatic transmission notably increased the relative risk reductions achieved by the intervention. These findings suggest prioritizing testing interventions for pathogens with high asymptomatic and pre-symptomatic transmission and highlight the symptomatic self-isolation rate as a policy intervention target.

Chapter Four: Projecting the Potential TB Cases Averted in High-Income Countries by Implementation of the Global Plan To End TB (2023-2030)

Justification: An increasing proportion of TB incidence in high-income countries (HICs) takes place among among foreign-born individuals who are infected in their country of origin. As a result, TB epidemiology in HICs is increasingly influenced by TB epidemiology in countries with high TB-burden. Objective: Our objective was to model the potential impact of implementation of The Global Plan To End TB (2023-2030) in WHO-designated countries with high TB-burden on TB incidence in HICs from 2023 to 2050. Methods: We modeled the impact of Global Plan implementation on TB incidence in HICs by constructing two sets of epidemiological models. First, we constructed models of TB incidence in countries with high TB-burden. Second, we used these high TB-burden country model outputs combined with projections of international migration to create epidemiological models of TB incidence among foreign-born individuals in HICs. We modeled two scenarios. In a “Current Trends” scenario, we assumed historical TB trends in each high TB-burden country would continue in the future. In a “Global Plan” scenario, we modeled the impact of achieving the Global Plan’s target of 80% incidence reduction between 2023 and 2030 in each high TB-burden country. For both scenarios we modelled the downstream effects on TB incidence in HICs. Main Results: Over the entire period 2023 – 2050, an estimated 873,663 (95% credible interval: 458,907 to 1,820,677) TB cases in HICs would be averted under the Global Plan Implementation scenario compared with the Current Trends scenario. Of this total, 241,101 (95% credible interval: 122,584 to 509,956) of these cases would be averted between 2023 and 2035, while 632,554 (95% credible interval: 336,316 to 1,310,718) would be averted between 2035 and 2050. Under the Global Plan scenario, TB incidence rates in the modeled HICs among foreign-born individuals would be 72% lower (95% credible interval: 58% to 83% lower) by 2035 and 92% lower (95% credible interval: 89% to 95% lower) by 2050 compared with the Current Trends scenario. Conclusions: Implementation of the Global Plan to End TB in high TB-burden countries would greatly reduce TB incidence among foreign born individuals in HICs, with the magnitude of health gains increasing over time.