Dynamics of the COVID-19 basic reproduction numbers in different countries.
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ABSTRACT:
SUBMITTER: Yue T
PROVIDER: S-EPMC7557808 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
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Dynamics of the COVID-19 basic reproduction numbers in different countries.
Yue Tianxiang T Fan Bin B Zhao Yapeng Y Wilson John P JP Du Zhengping Z Wang Qing Q Yin Xiaozhe X Duan Xiaonan X Zhao Na N Fan Zemeng Z Lin Hui H Zhou Chenghu C
Science bulletin 20201015 3
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Project description:Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number ℛ0, the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of ℛ0 relates to a herd immunity threshold (HIT), which is given by 1-1/ℛ0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level ℛ0 estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. ℛ0 estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21 January 2020 to 21 June 2020. Our ℛ0 estimates characterize the infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we found that no state had achieved herd immunity as of 20 September 2021.
| S-EPMC8780010 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) has become a life-threatening pandemic. The epidemic trends in different countries vary considerably due to different policy-making and resources mobilization. We calculated basic reproduction number (R0) and the time-varying estimate of the effective reproductive number (Rt) of COVID-19 by using the maximum likelihood method and the sequential Bayesian method, respectively. European and North American countries possessed higher R0 and unsteady Rt fluctuations, whereas some heavily affected Asian countries showed relatively low R0 and declining Rt now. The numbers of patients in Africa and Latin America are still low, but the potential risk of huge outbreaks cannot be ignored. Three scenarios were then simulated, generating distinct outcomes by using SEIR (susceptible, exposed, infectious, and removed) model. First, evidence-based prompt responses yield lower transmission rate followed by decreasing Rt. Second, implementation of effective control policies at a relatively late stage, in spite of huge casualties at early phase, can still achieve containment and mitigation. Third, wisely taking advantage of the time-window for developing countries in Africa and Latin America to adopt adequate measures can save more people's life. Our mathematical modeling provides evidence for international communities to develop sound design of containment and mitigation policies for COVID-19.
| S-EPMC7255828 | biostudies-literature
Project description:ObjectiveTo assess whether the basic reproduction number (R0) of COVID-19 is different across countries and what national-level demographic, social, and environmental factors other than interventions characterize initial vulnerability to the virus.MethodsWe fit logistic growth curves to reported daily case numbers, up to the first epidemic peak, for 58 countries for which 16 explanatory covariates are available. This fitting has been shown to robustly estimate R0 from the specified period. We then use a generalized additive model (GAM) to discern both linear and nonlinear effects, and include 5 random effect covariates to account for potential differences in testing and reporting that can bias the estimated R0.FindingsWe found that the mean R0 is 1.70 (S.D. 0.57), with a range between 1.10 (Ghana) and 3.52 (South Korea). We identified four factors-population between 20-34 years old (youth), population residing in urban agglomerates over 1 million (city), social media use to organize offline action (social media), and GINI income inequality-as having strong relationships with R0, across countries. An intermediate level of youth and GINI inequality are associated with high R0, (n-shape relationships), while high city population and high social media use are associated with high R0. Pollution, temperature, and humidity did not have strong relationships with R0 but were positive.ConclusionCountries have different characteristics that predispose them to greater intrinsic vulnerability to COVID-19. Studies that aim to measure the effectiveness of interventions across locations should account for these baseline differences in social and demographic characteristics.
| S-EPMC8189449 | biostudies-literature
Project description:The SIR ('susceptible-infectious-recovered') formulation is used to uncover the generic spread mechanisms observed by COVID-19 dynamics globally, especially in the early phases of infectious spread. During this early period, potential controls were not effectively put in place or enforced in many countries. Hence, the early phases of COVID-19 spread in countries where controls were weak offer a unique perspective on the ensemble-behavior of COVID-19 basic reproduction number Ro inferred from SIR formulation. The work here shows that there is global convergence (i.e., across many nations) to an uncontrolled Ro = 4.5 that describes the early time spread of COVID-19. This value is in agreement with independent estimates from other sources reviewed here and adds to the growing consensus that the early estimate of Ro = 2.2 adopted by the World Health Organization is low. A reconciliation between power-law and exponential growth predictions is also featured within the confines of the SIR formulation. The effects of testing ramp-up and the role of 'super-spreaders' on the inference of Ro are analyzed using idealized scenarios. Implications for evaluating potential control strategies from this uncontrolled Ro are briefly discussed in the context of the maximum possible infected fraction of the population (needed to assess health care capacity) and mortality (especially in the USA given diverging projections). Model results indicate that if intervention measures still result in Ro > 2.7 within 44 days after first infection, intervention is unlikely to be effective in general for COVID-19.
| S-EPMC7514051 | biostudies-literature
Project description:The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31-4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions.
| S-EPMC8880647 | biostudies-literature
Project description:Prisons have been hotspots for COVID-19 and likely an important driver of racial disparity in disease burden. From the first COVID-19 case detected through March 25, 2022, 66,684 of 196,652 residents of California's state prison system were infected, most of them in two large winter waves of outbreaks that reached all 35 of the state prisons. We used individual-level data on disease timing and nightly room assignments in these prisons to reconstruct locations and pathways of transmission statistically, and from that estimated reproduction numbers, locations of unobserved infection events, and the subsequent magnitude and distribution of long COVID prevalence. Where earlier work has recommended smaller cells over large dormitory housing to reduce transmission, recommended use of cells with solid doors over those with bars only, and cautioned against reliance on solid doors (e.g., in cold months when HVAC systems can circulate aerosols), we found evidence of substantial transmission in both dorms and cells regardless of the door and season. Effective reproduction numbers were found to range largely between 0 and 5, in both cells and dorms of all door types. Our estimates of excess case rates suggest that as a result of disparities in incarceration, prison outbreaks contributed to disproportionate disease burden on Black and Indigenous people in California. We estimated that 9,100-11,000 people have developed long COVID as a result of infection in these prison outbreaks, 1,700-2,000 of them with disabling consequences, and that this burden is disproportionately on Black and Indigenous people in comparison to the state as a whole. We urge high-quality medical care for prison residents affected by long COVID, and decarceration to reduce the risk of future outbreaks of both COVID-19 and other diseases.
| S-EPMC11703306 | biostudies-literature
Project description:ObjectiveTo estimate the basic reproduction number (R0) for COVID-19 in Western Europe.MethodsData (official statistics) on the cumulative incidence of COVID-19 at the start of the outbreak (before any confinement rules were declared) were retrieved in the 15 largest countries in Western Europe, allowing us to estimate the exponential growth rate of the disease. The rate was then combined with estimates of the distribution of the generation interval as reconstructed from the literature.ResultsDespite the possible unreliability of some official statistics about COVID-19, the spread of the disease appears to be remarkably similar in most European countries, allowing us to estimate an average R0 in Western Europe of 2.2 (95% CI: 1.9-2.6).ConclusionsThe value of R0 for COVID-19 in Western Europe appears to be significantly lower than that in China. The proportion of immune persons in the European population required to stop the outbreak could thus be closer to 50% than to 70%.
| S-EPMC7968714 | biostudies-literature
Project description:Mouse hepatitis virus (MHV) is a murine coronavirus and one of the most important pathogens in laboratory mice. Although various strains of MHV have been isolated, they are generally excreted in the feces and transmitted oronasally via aerosols and contaminated bedding. In this study, we attempted to determine the basic reproduction numbers (R0 ) of three strains of MHV to improve our understanding of MHV infections in mice. Five-week-old female C57BL/6J mice were inoculated intranasally with either the Y, NuU, or JHM variant strain of MHV and housed with two naïve mice. After 4 weeks, the presence or absence of anti-MHV antibody in the mice was determined by ELISA. We also examined the distribution of MHV in the organs of Y, NuU, or JHM variant-infected mice. Our data suggest that the transmissibility of MHV is correlated with viral growth in the gastrointestinal tract of infected mice. To the best of our knowledge, this is the first report to address the basic reproduction numbers among pathogens in laboratory animals.
| S-EPMC9306726 | biostudies-literature
Project description:Estimating the changes of epidemiological parameters, such as instantaneous reproduction number, Rt, is important for understanding the transmission dynamics of infectious diseases. Current estimates of time-varying epidemiological parameters often face problems such as lagging observations, averaging inference, and improper quantification of uncertainties. To address these problems, we propose a Bayesian data assimilation framework for time-varying parameter estimation. Specifically, this framework is applied to estimate the instantaneous reproduction number Rt during emerging epidemics, resulting in the state-of-the-art 'DARt' system. With DARt, time misalignment caused by lagging observations is tackled by incorporating observation delays into the joint inference of infections and Rt; the drawback of averaging is overcome by instantaneously updating upon new observations and developing a model selection mechanism that captures abrupt changes; the uncertainty is quantified and reduced by employing Bayesian smoothing. We validate the performance of DARt and demonstrate its power in describing the transmission dynamics of COVID-19. The proposed approach provides a promising solution for making accurate and timely estimation for transmission dynamics based on reported data.
| S-EPMC8923496 | biostudies-literature
Project description:ObjectiveThis study uses four COVID-19 outbreaks as examples to calculate and compare merits and demerits, as well as applicational scenarios, of three methods for calculating reproduction numbers.MethodThe epidemiological characteristics of the COVID-19 outbreaks are described. Through the definition method, the next-generation matrix-based method, and the epidemic curve and serial interval (SI)-based method, corresponding reproduction numbers were obtained and compared.ResultsReproduction numbers (R eff ), obtained by the definition method of the four regions, are 1.20, 1.14, 1.66, and 1.12. Through the next generation matrix method, in region H R eff = 4.30, 0.44; region P R eff = 6.5, 1.39, 0; region X R eff = 6.82, 1.39, 0; and region Z R eff = 2.99, 0.65. Time-varying reproduction numbers (R t ), which are attained by SI of onset dates, are decreasing with time. Region H reached its highest R t = 2.8 on July 29 and decreased to R t < 1 after August 4; region P reached its highest R t = 5.8 on September 9 and dropped to R t < 1 by September 14; region X had a fluctuation in the R t and R t < 1 after September 22; R t in region Z reached a maximum of 1.8 on September 15 and decreased continuously to R t < 1 on September 19.ConclusionThe reproduction number obtained by the definition method is optimal in the early stage of epidemics with a small number of cases that have clear transmission chains to predict the trend of epidemics accurately. The effective reproduction number R eff , calculated by the next generation matrix, could assess the scale of the epidemic and be used to evaluate the effectiveness of prevention and control measures used in epidemics with a large number of cases. Time-varying reproduction number R t , obtained via epidemic curve and SI, can give a clear picture of the change in transmissibility over time, but the conditions of use are more rigorous, requiring a greater sample size and clear transmission chains to perform the calculation. The rational use of the three methods for reproduction numbers plays a role in the further study of the transmissibility of COVID-19.
| S-EPMC9849755 | biostudies-literature