The public health impact of Paxlovid COVID-19 treatment in the United States (preprint)

The antiviral drug Paxlovid has been shown to rapidly reduce viral load. Coupled with vaccination, timely administration of safe and effective antivirals could provide a path towards managing COVID-19 without restrictive non-pharmaceutical measures. Here, we estimate the population-level impacts of expanding treatment with Paxlovid in the US using a multi-scale mathematical model of SARS-CoV-2 transmission that incorporates the within-host viral load dynamics of the Omicron variant. We find that, under a low transmission scenario (Re~1.2) treating 20% of symptomatic cases with Paxlovid would be life and cost saving, leading to an estimated 0.26 (95% CrI:0.03, 0.59) million hospitalizations averted, 30.61 (95% CrI:1.69, 71.15) thousand deaths averted, and US$52.16 (95% CrI:2.62, 122.63) billion reduction in the US. Rapid and broad use of the antiviral Paxlovid could substantially reduce COVID-19 morbidity and mortality, while averting socioeconomic hardship.

Global seasonal activities of respiratory syncytial virus before the COVID-19 pandemic: a systematic review (preprint)

Background: Varied seasonal patterns of respiratory syncytial virus (RSV) have been reported worldwide. We aimed to review the patterns of RSV activity globally before the COVID-19 pandemic and to explore factors potentially associated with RSV seasonality. Methods: We conducted a systematic review on articles identified in PubMed reporting RSV seasonality based on data collected before 1 January 2020. Information on the timing of the start, peak, and end of an RSV season, study location, study period, and details in study methods were extracted. RSV seasonal patterns were examined by geographic location, calendar month, analytic method and meteorological factors including temperature and absolute humidity. Correlation and regression analyses were conducted to explore the relationship between RSV seasonality and study methods and characteristics of study locations. Results: RSV seasons were reported in 209 articles published in 1973-2023 for 317 locations in 77 countries. Variations were identified in types of data, data collection and analytical methods across the studies. Regular RSV seasons were similarly reported in countries in temperate regions, with highly variable seasons identified in subtropical and tropical countries. Durations of RSV seasons were relatively longer in subtropical and tropical regions than from temperate regions. Longer durations of RSV seasons were associated with a higher daily average mean temperature and daily average mean absolute humidity. Conclusions: The global seasonal patterns of RSV provided important information for optimizing interventions against RSV infection. Heterogeneity in study methods highlighted the importance of developing and applying standardized approaches in RSV surveillance and data reporting.

Characterizing human collective behaviours of COVID-19 in Hong Kong (preprint)

People are likely to engage in collective behaviour online during extreme events, such as the COVID-19 crisis, to express their awareness, actions and concerns. Hong Kong has implemented stringent public health and social measures (PHSMs) to curb COVID-19 epidemic waves since the first COVID-19 case was confirmed on 22 January 2020. People are likely to engage in collective behaviour online during extreme events, such as the COVID-19 crisis, to express their awareness, actions and concerns. Here, we offer a framework to evaluate interactions among individuals emotions, perception, and online behaviours in Hong Kong during the first two waves (February to June 2020) and found a strong correlation between online behaviours of Google search and the real-time reproduction numbers. To validate the model output of risk perception, we conducted 10 rounds of cross-sectional telephone surveys from February 1 through June 20 in 2020 to quantify risk perception levels over time. Compared with the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people risk perception (individuals who worried about being infected) during the studied period. We may need to reinvigorate the public by engaging people as part of the solution to live their lives with reduced risk.

Predictive efficacies of vaccine dose fractionation using neutralizing antibody levels (preprint)

Background With the emergence of SARS-CoV-2 variants that eluded immunity from vaccines and prior infections, vaccine shortages and their effectiveness pose unprecedented challenges for governments to expand booster vaccination programs. Fractionation of vaccine doses might be an effective strategy to help society to face these challenges, which may have comparable efficacies in contrast with the standard doses. Methods In this study, we analyzed the relationship between in-vitro neutralization levels and the observed efficacies against asymptomatic and symptomatic infection of ten types of COVID-19 vaccines using data from 13 studies from vaccination and convalescent cohorts. We further projected efficacies for fractional doses based on 51 studies included in our systematic review. Results By comparing with the convalescent level, vaccine efficacy increases from 8.8% (95% CI: 1.4%, 16.1%) to 71.8% (95% CI: 63.0%, 80.7%) against asymptomatic infection, and from 33.6% (95% CI: 23.6%, 43.6%) to 98.6% (95% CI: 97.6%, 99.7%) against symptomatic infection, respectively, along with the mean neutralization level from 0.1 to 10 folds of convalescent level. And mRNA vaccines provide the strongest protection, and decrease slowly for fractional dosing between 50% and 100% dosage. Conclusions Our results are consistent with studies for immune protection from COVID-19 infection. Based on our study, we expect that fractional dose vaccination could provide a partial immunity for SARS-CoV-2 virus. Fractional doses of vaccines could be a viable vaccination strategy compared to full-dose vaccination and deserves further exploration. Key points We analyzed the relationship between neutralization levels and efficacies against asymptomatic and symptomatic infection of ten types of COVID-19 vaccines from convalescent cohorts. Fractional doses of vaccines could be a viable strategy compared to full-dose vaccination and deserves further exploration.

Insights into COVID-19 epidemiology and control from temporal changes in serial interval distributions in Hong Kong (preprint)

The serial interval distribution is used to approximate the generation time distribution, an essential parameter to predict the effective reproductive number "Rt", a measure of transmissibility. However, serial interval distributions may change as an epidemic progresses rather than remaining constant. Here we show that serial intervals in Hong Kong varied over time, closely associated with the temporal variation in COVID-19 case profiles and public health and social measures that were implemented in response to surges in community transmission. Quantification of the variation over time in serial intervals led to improved estimation of Rt, and provided additional insights into the impact of public health measures on transmission of infections. One-Sentence SummaryReal-time estimates of serial interval distributions can improve assessment of COVID-19 transmission dynamics and control.

Inferring time-varying generation time, serial interval and incubation period distributions for COVID-19 (preprint)

The generation time distribution, reflecting the time between successive infections in transmission chains, is a key epidemiological parameter for describing COVID-19 transmission dynamics. However, because exact infection times are rarely known, it is often approximated by the serial interval distribution. This approximation holds under the assumption that infectors and infectees share the same incubation period distribution, which may not always be true. We investigated incubation period and serial interval distributions in data on 2989 confirmed cases in China in January-February 2020, and developed an inferential framework to estimate the generation time distribution that accounts for variation over time due to changes in epidemiology, sampling biases and public health and social measures. We identified substantial reductions over time in the serial interval and generation time distributions. Our proposed method provides more reliable estimation of the temporal variation in the generation time distribution, improving assessment of transmission dynamics.

Inferring time-varying generation time, serial interval and incubation period distributions for COVID-19 (preprint)

Background The generation time distribution, reflecting the time between successive infections in transmission chains, is one of the fundamental epidemiological parameters for describing COVID-19 transmission dynamics. However, because exact infection times are rarely known, it is often approximated by the serial interval distribution, reflecting the time between illness onsets of infector and infectee. This approximation holds under the assumption that infectors and infectees share the same incubation period distribution, which may not always be true. Methods We analyzed data on observed incubation period and serial interval distributions in China, during January and February 2020, under different sampling approaches, and developed an inferential framework to estimate the generation time distribution that accounts for variation over time due to changes in epidemiology, sampling biases and public health and social measures. Results We analyzed data on a total of 2989 confirmed cases for COVID-19 during January 1 to February 29, 2020 in Mainland China. During the study period, the empirical forward serial interval decreased from a mean of 8.90 days to 2.68 days. The estimated mean backward incubation period of infectors increased from 3.77 days to 9.61 days, and the mean forward incubation period of infectees also increased from 5.39 days to 7.21 days. The estimated mean forward generation time decreased from 7.27 days (95% confidence interval: 6.42, 8.07) to 4.21 days (95% confidence interval: 3.70, 4.74) days by January 29. We used simulations to examine the sensitivity of our modelling approach to a number of assumptions and alternative dynamics. Conclusions The proposed method can provide more reliable estimation of the temporal variation in the generation time distribution, enabling proper assessment of transmission dynamics.

Time-varying transmission heterogeneity of SARS and COVID-19 in Hong Kong (preprint)

Transmission heterogeneity is a notable feature of the severe acute respiratory syndrome (SARS) and coronavirus disease 2019 (COVID-19) epidemics, though previous efforts to estimate how heterogeneity changes over time are limited. Using contact tracing data, we compared the epidemiology of SARS and COVID-19 infection in Hong Kong in 2003 and 2020-21 and estimated time-varying transmission heterogeneity (kt) by fitting negative binomial models to offspring distributions generated across variable observation windows. kt fluctuated over time for both COVID-19 and SARS on a continuous scale though SARS exhibited significantly greater (p < 0.001) heterogeneity compared to COVID-19 overall and in-time. For COVID-19, kt declined over time and was significantly associated with increasingly stringent non-pharmaceutical interventions though similar evidence for SARS was inconclusive. Underdetection of sporadic COVID-19 cases led to a moderate overestimation of kt, indicating COVID-19 heterogeneity of could be greater than observed. Time-varying or real-time estimates of transmission heterogeneity could become a critical indicator for epidemic intelligence in the future.

The risk of SARS-CoV-2 Omicron variant emergence in low and middle-income countries (LMICs) (preprint)

We estimated the probability of undetected emergence of the SARS-CoV-2 Omicron variant in 25 low and middle-income countries (LMICs) prior to December 5, 2021. In nine countries, the risk exceeds 50%; in Turkey, Pakistan and the Philippines, it exceeds 99%. Risks are generally lower in the Americas than Europe or Asia.

Superspreading of SARS-CoV-2 infections: A Systematic Review and Meta-analysis (preprint)

Superspreading in transmission is a feature of SARS-CoV-2 transmission. We conducted a systematic review and meta-analysis on globally reported dispersion parameters of SARS-CoV-2. The pooled estimate was 0.55 (95% CI: 0.30, 0.79). The study location and method were found to be important drivers for its diversity.

International risk of SARS-CoV-2 Omicron variant importations originating in South Africa (preprint)

Omicron, a fast-spreading SARS-CoV-2 variant of concern reported to the World Health Organization on November 24, 2021, has raised international alarm. We estimated there is at least 50% chance that Omicron had been introduced by travelers from South Africa into all of the 30 countries studied by November 27, 2021.

SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 - January 2021 (preprint)

IntroductionWe aimed to examine how public health policies influenced the dynamics of COVID-19 time-varying reproductive number (Rt) in South Carolina from February 26, 2020 to January 1, 2021. MethodsCOVID-19 case series (March 6, 2020 - January 10, 2021) were shifted by 9 days to approximate the infection date. We analyzed the effects of state and county policies on Rt using EpiEstim. We performed linear regression to evaluate if per-capita cumulative case count varies across counties with different population size. ResultsRt shifted from 2-3 in March to <1 during April and May. Rt rose over the summer and stayed between 1.4 and 0.7. The introduction of statewide mask mandates was associated with a decline in Rt (-15.3%; 95% CrI, -13.6%, -16.8%), and school re-opening, an increase by 12.3% (95% CrI, 10.1%, 14.4%). Less densely populated counties had higher attack rate (p<0.0001). ConclusionThe Rt dynamics over time indicated that public health interventions substantially slowed COVID-19 transmission in South Carolina, while their relaxation may have promoted further transmission. Policies encouraging people to stay home, such as closing non-essential businesses, were associated with Rt reduction, while policies that encouraged more movement, such as re-opening schools, were associated with Rt increase.

Comparative cost-effectiveness of SARS-CoV-2 vaccine dose fractionation in India: a modelling study (preprint)

Given constrained vaccine supplies globally, fractionation of vaccine doses may be an effective strategy for reducing disease and healthcare burdens, even with the emergence of COVID-19 variants. Using a multi-scale model that incorporates population-level transmission and individual-level vaccination, we estimate the costs associated with hospitalization, vaccine costs, and the economic benefit of reducing COVID-19 deaths associated with dose-fractionation strategies. Assuming a willingness-to-pay of US$10,517 per averted year of life lost (YLL) and a price of $12 per vaccine, under various transmission scenarios, with effective reproduction numbers ranging from 1.1 to 5.0 and with vaccine efficacy against transmission from 52% to 91%, the optimal vaccination strategy would always involve fractional doses of vaccines. Vaccine dose fractionation is a cost-effective strategy for mitigating the COVID-19 pandemic and could save a large number of lives, even after the emergence of variants with higher transmissibility.

Pandemic fatigue impedes mitigation of COVID-19 in Hong Kong (preprint)

Community-wide social distancing has been a cornerstone of pandemic control prior to mass vaccinations. The extent to which pandemic fatigue is undermining adherence to such measures and accelerating transmission remains unclear. Using large-scale weekly telephone surveys and mobility data, we characterize the evolution of risk perception and protective behaviours in Hong Kong. We estimate a 1.5% to 5.5% reduction in population compliance with protective policies for the fourth wave (October 2020 to January 2021) versus the third wave (July to August 2020), inducing prolonged disease circulation with increased infections. Mathematical models incorporating population protective behaviours estimates that the fourth wave would have been 14% smaller if not for pandemic fatigue. Mitigating pandemic fatigue is essential in maintaining population protective behaviours for controlling COVID-19.

The impacts of COVID-19 vaccine timing, number of doses, and risk prioritization on mortality in the US (preprint)

As COVID-19 vaccination begins worldwide, policymakers face critical trade-offs. Using a mathematical model of COVID-19 transmission, we find that timing of the rollout is expected to have a substantially greater impact on mortality than risk-based prioritization and adherence and that prioritizing first doses over second doses may be life saving.

International risk of the new variant COVID-19 importations originating in the United Kingdom (preprint)

A fast-spreading SARS-CoV-2 variant identified in the United Kingdom in December 2020 has raised international alarm. We estimate that, in all 15 countries analyzed, there is at least a 50% chance the variant was imported by travelers from the United Kingdom by December 7th.

Projecting the combined healthcare burden of seasonal influenza and COVID-19 (preprint)

The overlapping 2020-2021 influenza season and COVID-19 pandemic may overwhelm hospitals throughout the Northern Hemisphere. Using a mathematical model, we project that COVID-19 burden will dwarf that of influenza. If non-pharmacological mitigation efforts fail, increasing influenza vaccination coverage by 30% points would avert 54 hospitalizations per 100,000 people.

Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures (preprint)

Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including Frances ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

Projected COVID-19 epidemic in the United States in the context of the effectiveness of a potential vaccine and implications for social distancing and face mask use (preprint)

BackgroundMultiple candidates of COVID-19 vaccines have entered Phase III clinical trials in the United States (US). There is growing optimism that social distancing restrictions and face mask requirements could be eased with widespread vaccine adoption soon. MethodsWe developed a dynamic compartmental model of COVID-19 transmission for the four most severely affected states (New York, Texas, Florida, and California). We evaluated the vaccine effectiveness and coverage required to suppress the COVID-19 epidemic in scenarios when social contact was to return to pre-pandemic levels and face mask use was reduced. Daily and cumulative COVID-19 infection and death cases were obtained from the Johns Hopkins University Coronavirus resource center and used for model calibration. ResultsWithout a vaccine, the spread of COVID-19 could be suppressed in these states by maintaining strict social distancing measures and face mask use levels. But relaxing social distancing restrictions to the pre-pandemic level without changing the current face mask use would lead to a new COVID-19 outbreak, resulting in 0.8-4 million infections and 15,000-240,000 deaths across these four states over the next 12 months. In this scenario, introducing a vaccine would partially offset this negative impact even if the vaccine effectiveness and coverage are relatively low. However, if face mask use is reduced by 50%, a vaccine that is only 50% effective (weak vaccine) would require coverage of 55-94% to suppress the epidemic in these states. A vaccine that is 80% effective (moderate vaccine) would only require 32-57% coverage to suppress the epidemic. In contrast, if face mask usage stops completely, a weak vaccine would not suppress the epidemic, and further major outbreaks would occur. A moderate vaccine with coverage of 48-78% or a strong vaccine (100% effective) with coverage of 33-58% would be required to suppress the epidemic. Delaying vaccination rollout for 1-2 months would not substantially alter the epidemic trend if the current interventions are maintained. ConclusionsThe degree to which the US population can relax social distancing restrictions and face mask use will depend greatly on the effectiveness and coverage of a potential COVID-19 vaccine if future epidemics are to be prevented. Only a highly effective vaccine will enable the US population to return to life as it was before the pandemic.

The impact of asymptomatic COVID-19 infections on future pandemic waves (preprint)

The prevalence of asymptomatic COVID-19 infections is largely unknown and may determine the course of future pandemic waves and the effectiveness of interventions. Using an epidemiological model fit to COVID-19 hospitalization counts from New York City, New York and Austin, Texas, we found that the undocumented attack rate in the first pandemic wave depends on the proportion of asymptomatic infections but not on the infectiousness of such individuals. Based on a recent report that 22.7% of New Yorkers are seropositive for SARS-CoV-2, we estimate that 56% (95% CI: 53-59%) of COVID-19 infections are asymptomatic. Given uncertainty in the case hospitalization rate, however, the asymptomatic proportion could be as low as 20% or as high as 80%. We find that at most 1.26% of the Austin population was infected by April 27, 2020 and conclude that immunity from undetected infections is unlikely to slow future pandemic spread in most US cities in the summer of 2020.