Comparative profile for COVID-19 cases from China and North America: Clinical symptoms, comorbidities and disease biomarkers

BACKGROUND Large inter-individual and inter-population differences in the susceptibility to and outcome of severe acute respiratory syndrome coronavirus 2 or coronavirus disease 2019(COVID-19)have been noted.Understanding these differences and how they influence vulnerability to infection and disease severity is critical to public health intervention.AIM To analyze and compare the profile of COVID-19 cases between China and North America as two regions that differ in many environmental,host and healthcare factors related to disease risk.METHODS We conducted a meta-analysis to examine and compare demographic information,clinical symptoms,comorbidities,disease severity and levels of disease biomarkers of COVID-19 cases from clinical studies and data from China(105 studies)and North America(19 studies).RESULTS COVID-19 patients from North America were older than their Chinese counterparts and with higher male:Female ratio.Fever,cough,fatigue and dyspnea were the most common clinical symptoms in both study regions(present in about 30%to 75%of the cases in both regions).Meta-analysis for the prevalence of comorbidities(such as obesity,hypertension,diabetes,cardiovascular diseases,chronic obstructive pulmonary disease,cancer,and chronic kidney diseases)in COVID-19 patients were all significantly more prevalent in North America compared to China.Comorbidities were positively correlated with age but at a significantly younger age range in China compared to North American.The most prevalent infection outcome was acute respiratory distress syndrome which was 2-fold more frequent in North America than in China.Levels of C-reactive protein were 4.5-fold higher in the North American cases than in cases from China.CONCLUSION The differences in the profile of COVID-19 cases from China and North America may relate to differences in environmental-,host-and healthcare-related factors between the two regions.Such inter-population differences-together with intrapopulation variability-underline the need to characterize the effect of health inequities and inequalities on public health response to COVID-19 and can assist in preparing for the re-emergence of the epidemic.

Identifying the impediments and enablers of ecohealth for a case study on health and environmental sanitation in Hà Nam, Vietnam

Background:To date,research has shown an increasing use of the term“ecohealth”in literature,but few researchers have explicitly described how it has been used.We investigated a project on health and environmental sanitation(the conceptual framework of which included the pillars of ecohealth)to identify the impediments and enablers of ecohealth and investigate how it can move from concept to practice.Methods:A case study approach was used.The interview questions were centred on the nature of interactions and the sharing of information between stakeholders.Results:The analysis identified nine impediments and 15 enablers of ecohealth.Three themes relating to impediments,in particular-integration is not clear,don’t understand,and limited participation-related more directly to the challenges in applying the ecohealth pillars of transdisciplinarity and participation.The themes relating to enablers-awareness and understanding,capacity development,and interactions-facilitated usage of the research results.By extracting information on the environmental,social,economic,and health aspects of environmental sanitation,we found that the issue spanned multiple scales and sectors.Conclusion:The challenge of how to integrate these aspects should be considered at the design stage and throughout the research process.We recommend that ecohealth research teams include a self-investigation of their processes in order to facilitate a comparison of moving from concept to practice,which may offer insights into how to evaluate the process.

Exploring the percentage of COVID-19 cases reported in the community in Canada and associated case fatality ratios

While surveillance can identify changes in COVID-19 transmission patterns over time and space,sections of the population at risk,and the efficacy of public health measures,reported cases of COVID-19 are generally understood to only capture a subset of the actual number of cases.Our primary objective was to estimate the percentage of cases reported in the general community,considered as those that occurred outside of long-term care facilities(LTCFs),in specific provinces and Canada as a whole.We applied a methodology using the delay-adjusted case fatality ratio(CFR)to all cases and deaths,as well as those representing the general community.Our second objective was to assess whether the assumed CFR(mean=1.38%)was appropriate for calculating underestimation of cases in Canada.Estimates were developed for the period from March 11th,2020 to September 16th,2020.Estimates of the percentage of cases reported(PrCR)and CFR varied spatially and temporally across Canada.For the majority of provinces,and for Canada as a whole,the PrCR increased through the early stages of the pandemic.The estimated PrCR in general community settings for all of Canada increased from 18.1%to 69.0%throughout the entire study period.Estimates were greater when considering only those data from outside of LTCFs.The estimated upper bound CFR in general community settings for all of Canada decreased from 9.07%on March 11th,2020 to 2.00%on September 16th,2020.Therefore,the true CFR in the general community in Canada was likely less than 2%on September 16th.According to our analysis,some provinces,such as Alberta,Manitoba,Newfoundland and Labrador,Nova Scotia,and Saskatchewan reported a greater percentage of cases as of September 16th,compared to British Columbia,Ontario,and Quebec.This could be due to differences in testing rates and criteria,demographics,socioeconomic factors,race,and access to healthcare among the provinces.Further investigation into these factors could reveal differences among provinces that could partially explain the variation in estimates of PrCR and CFR identified in our study.The estimates provide context to the summative state of the pandemic in Canada,and can be improved as knowledge of COVID-19 reporting rates and disease characteristics are advanced.

A novel IDEA: The impact of serial interval on a modified- Incidence Decay and Exponential Adjustment (m-IDEA) model for projections of daily COVID-19 cases

The SARS-CoV-2 virus causes the disease COVID-19,and has caused high morbidity and mortality worldwide.Empirical models are useful tools to predict future trends of disease progression such as COVID-19 over the near-term.A modified Incidence Decay and Exponential Adjustment(m-IDEA)model was developed to predict the progression of infectious disease outbreaks.The modification allows for the production of precise daily estimates,which are critical during a pandemic of this scale for planning purposes.The m-IDEA model was employed using a range of serial intervals given the lack of knowledge on the true serial interval of COVID-19.Both deterministic and stochastic approaches were applied.Model fitting was accomplished through minimizing the sum-of-square differences between predicted and observed daily incidence case counts,and performance was retrospectively assessed.The performance of the m-IDEA for projection cases in the nearterm was improved using shorter serial intervals(1e4 days)at early stages of the pandemic,and longer serial intervals at mid-to late-stages(5e9 days)thus far.This,coupled with epidemiological reports,suggests that the serial interval of COVID-19 might increase as the pandemic progresses,which is rather intuitive:Increasing serial intervals can be attributed to gradual increases in public health interventions such as facility closures,public caution and social distancing,thus increasing the time between transmission events.In most cases,the stochastic approach captured the majority of future reported incidence data,because it accounts for the uncertainty around the serial interval of COVID-19.As such,it is the preferred approach for using the m-IDEA during dynamic situation such as in the midst of a major pandemic.

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.