Bidirectional impact of imperfect mask use on reproduction number of COVID-19:A next generation matrix approach

The use of masks as a means of reducing transmission of COVID-19 outside healthcare settings has proved controversial.Masks are thought to have two modes of effect:they prevent infection with COVID-19 in wearers;and prevent transmission by individuals with subclinical infection.We used a simple next-generation matrix approach to estimate the conditions under which masks would reduce the reproduction number of COVID-19 under a threshold of 1.Our model takes into account the possibility of assortative mixing,where mask users interact preferentially with other mask users.We make 3 key observations:1.Masks,even with suboptimal efficacy in both prevention of acquisition and transmission of infection,could substantially decrease the reproduction number for COVID-19 if widely used.2.Widespread masking may be sufficient to suppress epidemics where R has been brought close to 1 via other measures(e.g.,distancing).3.“Assortment”within populations(the tendency for interactions between masked individuals to be more likely than interactions between masked and unmasked individuals)would rapidly erode the impact of masks.As such,mask uptake needs to be fairly universal to have an effect.This simple model suggests that widespread uptake of masking could be determinative in suppressing COVID-19 epidemics in regions with R(t)at or near 1.

Yellow fever virus outbreak in Brazil under current and future climate

Introduction:Yellow fever(YF)is primarily transmitted by Haemagogus species of mosquitoes.Under climate change,mosquitoes and the pathogens that they carry are expected to develop faster,potentially impacting the case count and duration of YF outbreaks.The aim of this study was to determine how YF virus outbreaks in Brazil may change under future climate,using ensemble simulations from regional climate models under RCP4.5 and RCP8.5 scenarios for three time periods:2011-2040(short-term),2041-2070(mid-term),and 2071-2100(long-term).Methods:A compartmental model was developed to fit the 2017/18 YF outbreak data in Brazil using least squares optimization.To explore the impact of climate change,temperature-sensitive mosquito parameters were set to change over projected time periods using polynomial equations fitted to their relationship with temperature according to the average temperature for years 2011-2040,2041-2070,and 2071-2100 for climate change scenarios using RCP4.5 and RCP8.5,where RCP4.5/RCP8.5 corresponds to intermediate/high radiative forcing values and to moderate/higher warming trends.A sensitivity analysis was conducted to determine how the temperature-sensitive parameters impacted model results,and to determine how vaccination could play a role in reducing YF in Brazil.Results:Yellow fever case projections for Brazil from the models varied when climate change scenarios were applied,including the peak clinical case incidence,cumulative clinical case incidence,time to peak incidence,and the outbreak duration.Overall,a decrease in YF cases and outbreak duration was observed.Comparing the observed incidence in 2017/18 to the projected incidence in 2070-2100,for RCP4.5,the cumulative case incidence decreased from 184 to 161,and the outbreak duration decreased from 21 to 20 weeks.For RCP8.5,the peak case incidence decreased from 184 to 147,and the outbreak duration decreased from 21 to 17 weeks.The observed decrease was primarily due to temperature increasing beyond that suitable for Haemagogus mosquito survival.Conclusions:Climate change is anticipated to have an impact on mosquito-borne diseases.We found outbreaks of YF may reduce in intensity as temperatures increase in Brazil;however,temperature is not the only factor involved with disease transmission.Other factors must be explored to determine the attributable impact of climate change on mosquito-borne diseases.

Within-host model of respiratory virus shedding and antibody response to H9N2 avian influenza virus vaccination and infection in chickens

Avian influenza virus(AIV)H9N2 subtype is an infectious pathogen that can affect both the respiratory and gastrointestinal systems in chickens and continues to have an important economic impact on the poultry industry.While the host innate immune response provides control of virus replication in early infection,the adaptive immune response aids to clear infections and prevent future invasion.Modelling virus-innate immune response pathways can improve our understanding of early infection dynamics and help to guide our understanding of virus shedding dynamics that could lead to reduced transmission between hosts.While some countries use vaccines for the prevention of H9N2 AIV in poultry,the virus continues to be endemic in regions of Eurasia and Africa,indicating a need for improved vaccine efficacy or vaccination strategies.Here we explored how three type-I interferon(IFN)pathways affect respiratory virus shedding patterns in infected chickens using a within-host model.Additionally,prime and boost vaccination strategies for a candidate H9N2 AIV vaccine are assessed for the ability to elicit seroprotective antibody titres.The model demonstrates that inclusion of virus sensitivity to intracellular type-I IFN pathways results in a shedding pattern most consistent with virus titres observed in infected chickens,and the inclusion of a cellular latent period does not improve model fit.Furthermore,early administration of a booster dose two weeks after the initial vaccine is administered results in seroprotective titres for the greatest length of time for both broilers and layers.These results demonstrate that type-I IFN intracellular mechanisms are required in a model of respiratory virus shedding in H9N2 AIV infected chickens,and also highlights the need for improved vaccination strategies for laying hens.