scholarly journals SARS-CoV-2 shifting transmission dynamics and hidden reservoirs potentially limit efficacy of public health interventions in Italy

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Marta Giovanetti ◽  
Eleonora Cella ◽  
Francesca Benedetti ◽  
Brittany Rife Magalis ◽  
Vagner Fonseca ◽  
...  

AbstractWe investigated SARS-CoV-2 transmission dynamics in Italy, one of the countries hit hardest by the pandemic, using phylodynamic analysis of viral genetic and epidemiological data. We observed the co-circulation of multiple SARS-CoV-2 lineages over time, which were linked to multiple importations and characterized by large transmission clusters concomitant with a high number of infections. Subsequent implementation of a three-phase nationwide lockdown strategy greatly reduced infection numbers and hospitalizations. Yet we present evidence of sustained viral spread among sporadic clusters acting as “hidden reservoirs” during summer 2020. Mathematical modelling shows that increased mobility among residents eventually catalyzed the coalescence of such clusters, thus driving up the number of infections and initiating a new epidemic wave. Our results suggest that the efficacy of public health interventions is, ultimately, limited by the size and structure of epidemic reservoirs, which may warrant prioritization during vaccine deployment.

2020 ◽  
Author(s):  
Marta Giovanetti ◽  
Eleonora Cella ◽  
Francesca Benedetti ◽  
Brittany Rife Magalis ◽  
Vagner Fonseca ◽  
...  

AbstractWe investigated SARS-CoV-2 transmission dynamics in Italy, one of the countries hit hardest by the pandemic, using phylodynamic analysis of viral genetic and epidemiological data. We observed the co-circulation of at least 13 different SARS-CoV-2 lineages over time, which were linked to multiple importations and characterized by large transmission clusters concomitant with a high number of infections. Subsequent implementation of a three-phase nationwide lockdown strategy greatly reduced infection numbers and hospitalizations. Yet we present evidence of sustained viral spread among sporadic clusters acting as “hidden reservoirs” during summer 2020. Mathematical modelling shows that increased mobility among residents eventually catalyzed the coalescence of such clusters, thus driving up the number of infections and initiating a new epidemic wave. Our results suggest that the efficacy of public health interventions is, ultimately, limited by the size and structure of epidemic reservoirs, which may warrant prioritization during vaccine deployment.


Author(s):  
Stephen J Beckett ◽  
Marian Dominguez-Mirazo ◽  
Seolha Lee ◽  
Clio Andris ◽  
Joshua S Weitz

Epidemiological forecasts of COVID-19 spread at the country and/or state level have helped shape public health interventions. However, such models leave a scale-gap between the spatial resolution of actionable information (i.e. the county or city level) and that of modeled viral spread. States and nations are not spatially homogeneous and different areas may vary in disease risk and severity. For example, COVID-19 has age-stratified risk. Similarly, ICU units, PPE and other vital equipment are not equally distributed within states. Here, we implement a county-level epidemiological framework to assess and forecast COVID-19 spread through Georgia, where 1,933 people have died from COVID-19 and 44,638 cases have been documented as of May 27, 2020. We find that county-level forecasts trained on heterogeneity due to clustered events can continue to predict epidemic spread over multi-week periods, potentially serving efforts to prepare medical resources, manage supply chains, and develop targeted public health interventions. We find that the premature removal of physical (social) distancing could lead to rapid increases in cases or the emergence of sustained plateaus of elevated fatalities.


2021 ◽  
Vol 13 (1) ◽  
pp. 19-36
Author(s):  
Rebecca Godard ◽  
Susan Holtzman

This study investigated polarization on Twitter related to the COVID-19 pandemic by examining tweets containing #Plandemic (suggests the pandemic is a hoax) or #StayHome (encourages compliance with health recommendations). Over 35,000 tweets from over 25,000 users were collected in April 2020 and examined using sentiment and social network analyses. Compared to #StayHome tweets, #Plandemic tweets came from a more tightly connected network, were higher in negative emotional content, and could be sub-divided into specific categories of misinformation and conspiracy theories. To evaluate the stability of users' COVID-related perspectives, the prevalence of pro- and anti-mask sentiment was measured in same users' tweets approximately four months later. Results revealed substantial stability over time, with 40% of #Plandemic users tweeting anti-mask hashtags compared to just 2% of #StayHome users. Findings demonstrate COVID-related polarization on Twitter and have implications for public health interventions to quell the propagation of misinformation.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Gage K. Moreno ◽  
Katarina M. Braun ◽  
Kasen K. Riemersma ◽  
Michael A. Martin ◽  
Peter J. Halfmann ◽  
...  

Abstract Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties following the statewide “Safer at Home” order, which went into effect 25 March 2020. Our results suggest patterns of SARS-CoV-2 transmission may vary substantially even in nearby communities. Understanding these local patterns will enable better targeting of public health interventions.


2020 ◽  
Author(s):  
Erin Kirwin ◽  
Ellen Rafferty ◽  
Kate Harback ◽  
Jeff Round ◽  
Christopher McCabe

AbstractCoronavirus disease 2019 (COVID-19) is a severe, novel virus that has spread globally. The implementation of a combination of public health interventions is required to reduce viral spread and avoid overwhelming acute care systems. Once available, an effective vaccination will further mitigate the impact of the COVID-19 pandemic. However, decision makers will initially need to prioritise access to limited vaccine stockpiles as these will be insufficient to vaccine the whole population.The aim of this study is to identify optimal vaccine allocation strategies defined by age and risk target groups, coverage, effectiveness, and cost of vaccine, within a dynamic context where other public health responses and population behaviour change. In this study we use an epidemiological model of COVID-19 that has been enhanced to produce expected costs and Quality Adjusted Life Year results as well as total cases, hospitalisations, deaths, and net monetary benefit. We use the model to simulate hypothetical scenarios where vaccine is allocated beginning on October 15, 2020 with vaccine assumptions ranging from moderately optimistic to ‘worst-case scenario’. Net monetary benefit is used as the objective for optimisation.In a scenario with a sterilizing vaccine that is 80% effective, a stockpile sufficient for 40% population coverage, and prioritisation of those over the age of 60 at high risk of poor outcomes, active cases are reduced by 29.2% and net monetary benefit increased by $297 million dollars, relative to an identical scenario with no vaccine. The relative impact of prioritisation strategies varies greatly depending on concurrent public health interventions, for example, polices such as school closures and senior contact reductions have similar impacts on incremental net monetary benefit when there is no prioritisation given to any age or risk group (147 vs. 120 million, respectively), but when older and high risk groups are given priority, the benefit of school closures is much larger than reducing contacts for seniors (iNB 122 vs. 79 million, respectively). Results demonstrated that rank ordering of different prioritisation options varied greatly by prioritisation criteria, with different vaccine effectiveness and coverage, and by concurrently implemented policies.The results of this paper have three key policy implications: (i) that optimal vaccine allocation will depend on the public health policies, and human behaviours in place at the time of allocation; (ii) the outcomes of vaccine allocation policies can be greatly supported with interventions targeting contact reduction in critical sub-populations; and (iii) the identification of the optimal strategy depends on which outcomes are prioritised.


2015 ◽  
Vol 264 ◽  
pp. 38-53 ◽  
Author(s):  
Drew Posny ◽  
Jin Wang ◽  
Zindoga Mukandavire ◽  
Chairat Modnak

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