Agent-based modeling of the COVID-19 pandemic in Florida (preprint)

The onset of the COVID-19 pandemic drove a widespread, often uncoordinated effort by research groups to develop mathematical models of SARS-CoV-2 to study its spread and inform control efforts. The urgent demand for insight at the outset of the pandemic meant early models were typically either simple or repurposed from existing research agendas. Our group predominantly uses agent-based models (ABMs) to study fine-scale intervention scenarios. These high-resolution models are large, complex, require extensive empirical data, and are often more detailed than strictly necessary for answering qualitative questions like "Should we lockdown?" During the early stages of an extraordinary infectious disease crisis, particularly before clear empirical evidence is available, simpler models are more appropriate. As more detailed empirical evidence becomes available, however, and policy decisions become more nuanced and complex, fine-scale approaches like ours become more useful. In this manuscript, we discuss how our group navigated this transition as we modeled the pandemic. The role of modelers often included nearly real-time analysis, and the massive undertaking of adapting our tools quickly. We were often playing catch up with a firehose of evidence, while simultaneously struggling to do both academic research and real-time decision support, under conditions conducive to neither. By reflecting on our experiences of responding to the pandemic and what we learned from these challenges, we can better prepare for future demands.

Effectiveness of SARS-CoV-2 Vaccines against Omicron Infection and Severe Events: A Systematic Review and Meta-Analysis of Test-Negative Design Studies (preprint)

Background: Evaluating vaccine effectiveness (VE) of a full vaccine series and booster doses against COVID-19 is important for health decision-making. Methods: We systematically searched papers that evaluated VE of SARS-CoV-2 vaccines on PubMed, Web of Science, Cochrane Library, Google Scholar, Embase, Scopus, and preprint servers (bioRxiv and medRxiv) published from November 26th, 2021 to June 27th, 2022 (for full doses and first booster), and to January 8th, 2023 (for the second booster). The pooled VE against Omicron-associated symptomatic or any infection as well as severe events are estimated in a meta-analysis framework. Results: From 2,552 citations identified, a total of 42 were included. The vaccination of the first booster provided stronger protection against Omicron than the full doses alone, shown by the VE estimates of 53.1% (95% CI: 48.0-57.8) vs. 28.6% (95% CI: 18.5-37.4) against infection and 82.5% (95% CI: 77.8-86.2) vs. 57.3% (95% CI: 48.5-64.7) against severe disease. The second booster offered strong protection among adults within 60 days of vaccination against infection (VE=53.1%, 95% CI: 48.0-57.8) and severe disease (VE=87.3% (95% CI: 75.5-93.4), comparable to the first booster with corresponding VE estimates of 59.9% against infection and 84.8% against severe disease. The VEs of the booster doses against severe disease among adults sustained beyond 60 days, 77.6% (95% CI: 69.4-83.6) for the first and 85.9% (95% CI: 80.3-89.9) for the second booster. The VE against infection was less sustainable regardless of dose type. Pure mRNA vaccines provided comparable protection to partial mRNA vaccines, but both provided higher protection than non-mRNA vaccination. Conclusion: One or two booster doses of current SARS-CoV-2 vaccines provide considerable protection against Omicron infection and substantial and sustainable protection against Omicron-induced severe clinical outcomes.

Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study (preprint)

Access to COVID-19 vaccines on the global scale has been drastically impacted by structural socio-economic inequities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) sampled from all WHO regions. We focus on the first critical months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that, in this high vaccine availability scenario, more than 50% of deaths (min-max range: 56%-99%) that occurred in the analyzed countries could have been averted. We further consider a scenario where LMIC had similarly early access to vaccine doses as high income countries; even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: 7%-73%) could have been averted. In the absence of equitable allocation, the model suggests that considerable additional non-pharmaceutical interventions would have been required to offset the lack of vaccines (min-max range: 15%-75%). Overall, our results quantify the negative impacts of vaccines inequities and call for amplified global efforts to provide better access to vaccine programs in low and lower middle income countries

Updated projections for COVID-19 omicron wave in Florida (preprint)

In this report, we use a detailed simulation model to assess and project the COVID-19 epidemic in Florida. The model is a data-driven, stochastic, discrete-time, agent based model with an explicit representation of people and places. Using the model, we find that the omicron variant wave in Florida is likely to cause many more infections than occurred during the delta variant wave. Due to testing limitations and often mild symptoms, however, we anticipate that omicron infections will be underreported compared to delta. We project that reported cases of COVID-19 will continue to grow significantly and peak in early January 2022, and that the number of reported COVID-19 deaths due to omicron may be 1/3 of the total caused by the delta wave.

Efficacy Estimates for Various COVID-19 Vaccines: What we Know from the Literature and Reports (preprint)

In this report, we provide summary estimates, from publications and reports, of vaccine efficacy (VE) for the COVID-19 vaccines that are being rolled out on a global scale. We find that, on average, the efficacy against any disease with infection is 85% (95% CI: 71 - 93%) after a full course of vaccination. The VE against severe disease, hospitalization or death averages close to 100%. The average VE against infection, regardless of symptoms, is 84% (95% CI: 70 - 91%). We also find that the average VE against transmission to others for Infected vaccinated people is 54% (95% CI: 38 - 66%). Finally, we prove summary estimates of the VE against any disease with infection for some of the variants of concern (VOC). The average VE for the VOC B.1.1.7, B.1.1.28 (P1) and B.1.351 are 86% (95% CI: 65 - 84%), 61% (95% CI: 43 - 73%) and 56% (95% CI: 29 - 73%), respectively.

Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave in Europe and the United States (preprint)

Given the narrowness of the initial testing criteria, the SARS-CoV-2 virus spread through cryptic transmission in January and February, setting the stage for the epidemic wave experienced in March and April, 2020. We use a global metapopulation epidemic model to provide a mechanistic understanding of the global dynamic underlying the establishment of the COVID-19 pandemic in Europe and the United States (US). The model is calibrated on international case introductions at the early stage of the pandemic. We find that widespread community transmission of SARS-CoV-2 was likely in several areas of Europe and the US by January 2020, and estimate that by early March, only 1 - 3 in 100 SARS-CoV-2 infections were detected by surveillance systems. Modeling results indicate international travel as the key driver of the introduction of SARS-CoV-2 with possible importation and transmission events as early as December, 2019. We characterize the resulting heterogeneous spatio-temporal spread of SARS-CoV-2 and the burden of the first COVID-19 wave (February-July 2020). We estimate infection attack rates ranging from 0.78%-15.2% in the US and 0.19%-13.2% in Europe. The spatial modeling of SARS-CoV-2 introductions and spreading provides insights into the design of innovative, model-driven surveillance systems and preparedness plans that have a broader initial capacity and indication for testing.

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas (preprint)

Detailed characterization of SARS-CoV-2 transmission across different settings can help design less disruptive interventions. We used real-time, privacy-enhanced mobility data in the New York City and Seattle metropolitan areas to build a detailed agent-based model of SARS-CoV-2 infection to estimate the where, when, and magnitude of transmission events during the pandemics first wave. We estimate that only 18% of individuals produce most infections (80%), with about 10% of events that can be considered super-spreading events (SSEs). Although mass-gatherings present an important risk for SSEs, we estimate that the bulk of transmission occurred in smaller events in settings like workplaces, grocery stores, or food venues. The places most important for transmission change during the pandemic and are different across cities, signaling the large underlying behavioral component underneath them. Our modeling complements case studies and epidemiological data and indicates that real-time tracking of transmission events could help evaluate and define targeted mitigation policies.

Household transmission of SARS-CoV-2: a systematic review and meta-analysis of secondary attack rate (preprint)

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spread by direct, indirect, or close contact with infected people via infected respiratory droplets or saliva. Crowded indoor environments with sustained close contact and conversations are a particularly high-risk setting. MethodsWe performed a meta-analysis through July 29, 2020 of SARS-CoV-2 household secondary attack rate (SAR), disaggregating by several covariates (contact type, symptom status, adult/child contacts, contact sex, relationship to index case, index case sex, number of contacts in household, coronavirus). FindingsWe identified 40 relevant published studies that report household secondary transmission. The estimated overall household SAR was 18{middle dot}8% (95% confidence interval [CI]: 15{middle dot}4%-22{middle dot}2%), which is higher than previously observed SARs for SARS-CoV and MERS-CoV. We observed that household SARs were significantly higher from symptomatic index cases than asymptomatic index cases, to adult contacts than children contacts, to spouses than other family contacts, and in households with one contact than households with three or more contacts. InterpretationTo prevent the spread of SARS-CoV-2, people are being asked to stay at home worldwide. With suspected or confirmed infections referred to isolate at home, household transmission will continue to be a significant source of transmission.

Estimating the establishment of local transmission and the cryptic phase of the COVID-19 pandemic in the USA (preprint)

We use a global metapopulation transmission model to study the establishment of sustained and undetected community transmission of the COVID-19 epidemic in the United States. The model is calibrated on international case importations from mainland China and takes into account travel restrictions to and from international destinations. We estimate widespread community transmission of SARS-CoV-2 in February, 2020. Modeling results indicate international travel as the key driver of the introduction of SARS-CoV-2 in the West and East Coast metropolitan areas that could have been seeded as early as late-December, 2019. For most of the continental states the largest contribution of imported infections arrived through domestic travel flows.

Modeling the impact of social distancing, testing, contact tracing and household quarantine on second-wave scenarios of the COVID-19 epidemic (preprint)

The new coronavirus disease 2019 (COVID-19) has required the implementation of severe mobility restrictions and social distancing measures worldwide. While these measures have been proven effective in abating the epidemic in several countries, it is important to estimate the effectiveness of testing and tracing strategies to avoid a potential second wave of the COVID-19 epidemic. We integrate highly detailed (anonymized, privacy-enhanced) mobility data from mobile devices, with census and demographic data to build a detailed agent-based model to describe the transmission dynamics of SARS-CoV-2 in the Boston metropolitan area. We find that enforcing strict social distancing followed by a policy based on a robust level of testing, contact-tracing and household quarantine, could keep the disease at a level that does not exceed the capacity of the health care system. Assuming the identification of 50% of the symptomatic infections, and the tracing of 40% of their contacts and households, which corresponds to about 9% of individuals quarantined, the ensuing reduction in transmission allows the reopening of economic activities while attaining a manageable impact on the health care system. Our results show that a response system based on enhanced testing and contact tracing can play a major role in relaxing social distancing interventions in the absence of herd immunity against SARS-CoV-2.

Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study (preprint)

Background The COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy. Methods We collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level. Results The median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January. Conclusion Our findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

The effect of travel restrictions on the spread of the 2019 novel coronavirus (2019-nCoV) outbreak (preprint)

Motivated by the rapid spread of a novel coronavirus (2019-nCoV) in Mainland China, we use a global metapopulation disease transmission model to project the impact of both domestic and international travel limitations on the national and international spread of the epidemic. The model is calibrated on the evidence of internationally imported cases before the implementation of the travel quarantine of Wuhan. By assuming a generation time of 7.5 days, the reproduction number is estimated to be 2.4 [90% CI 2.2-2.6]. The median estimate for number of cases before the travel ban implementation on January 23, 2020 is 58,956 [90% CI 40,759 - 87,471] in Wuhan and 3,491 [90% CI 1,924 - 7,360] in other locations in Mainland China. The model shows that as of January 23, most Chinese cities had already received a considerable number of infected cases, and the travel quarantine delays the overall epidemic progression by only 3 to 5 days. The travel quarantine has a more marked effect at the international scale, where we estimate the number of case importations to be reduced by 80% until the end of February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.