Infectious Diseases eJournal最新文献

{"title":"Working Paper: Exceptionally Many Vulnerable – 'Dry Tinder' – in Sweden Prior to COVID-19","authors":"J. Herby","doi":"10.2139/ssrn.3702595","DOIUrl":"https://doi.org/10.2139/ssrn.3702595","url":null,"abstract":"Using monthly all-cause death tolls for Denmark, Sweden and Finland from January 1946 (and Norway from January 2000) to June 2020, I estimate the stock of vulnerable elderly with a high mortality risk – “dry tinder” – in each country primo each month from January 1960 to April 2020. \u0000 \u0000My calculations show that the stock of “dry tinder” in Sweden was very large compared to other Nordic countries going into the COVID-19-pandemic early April and large even in a historical perspective. The results are robust to different specifications of the expected mortality and the “dry tinder”-stock. \u0000 \u0000My results show that a large share of the excess mortality in Sweden in April 2020 may be partially explained by a vulnerable, elderly population due to very mild flu seasons in 18/19 and 19/20 as well as very few deaths during the 2019 summer compared to earlier years and compared to other Nordic countries. \u0000 \u0000My results illustrate – and I cannot stress this enough – that plain coincidences may be important when understanding the COVID-19-death toll in a country compared to national lockdown policies.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"2006 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127669361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting COVID-19 Unreported Case From Space","authors":"Yayan Satyakti","doi":"10.2139/ssrn.3697917","DOIUrl":"https://doi.org/10.2139/ssrn.3697917","url":null,"abstract":"This paper investigates how social behavior such as people responding to news and economic performance will influence on human mobility and confirming positive case of COVID-19. I employed news policy will reduce human mobility. Whereas, economic performance of income group proxied through night lights data. The mobility data retrieved from Waze Car Congestion Report according to hourly basis that located with spatial GPS. The confirmed case of COVID-19 were retrieved at provincial level These datasets are estimated with econometric epidemiologist model. The results found that without policy the spreading case of COVID-19 will increase about 8 million cases, whereas with policy the unreported COVID-19 confirmed case about 1.9 – 2 times of government publicly report. We conclude that literacy and awareness of COVID-19 is necessary to be important agenda rather than economy. The results indicates that Indonesian prefer to engaging with economic rather than health policy.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114647201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid COVID-19 Modeling Support for Regional Health Systems in England","authors":"Lidia Betcheva, F. Erhun, Antoine Feylessoufi, Paulo Gonçalves, Houyuan Jiang, P. Kattuman, Tom Pape, A. Pari, S. Scholtes, Carina S B Tyrrell","doi":"10.2139/ssrn.3695258","DOIUrl":"https://doi.org/10.2139/ssrn.3695258","url":null,"abstract":"Problem definition: This paper describes the real-time participatory modeling work that our team of academics, public health officials, and clinical decision-makers has been undertaking to support the regional efforts to tackle COVID-19 in the East of England. Methodology: Since March 2020, we have been studying four research questions that have allowed us to address the pandemic's current and near-future rapidly evolving epidemiological state, as well as the bed capacity demand in the short (a few weeks) and medium (several months) term. Frequent data input from and consultations with our public health and clinical partners allow our academic team to apply dynamic data-driven approaches using time series modeling, Bayesian estimation, and system dynamics modeling. We thus obtain a broad view of the evolving situation. Results: The academic team presents the model outcomes and insights during weekly joint meetings among public health services, national health services, and academics to support COVID-19 planning activities in the East of England, contributing to the discussion of the COVID-19 response and issues beyond immediate COVID-19 planning. Academic/practical relevance: As COVID-19 planning efforts necessitate rapid response, our portfolio of scratch models aims to achieve the right balance between rigor and speed in the face of an uncertain and changing situation. Managerial implications: Our regional and local focus enables us to better understand the pandemic's progression and to help decision-makers make more informed short- and medium-term capacity plans in different localities in the East of England. In addition, the learnings from our collaborative experiences may present guidance on how academics and practitioners can successfully collaborate in rapid response to disasters such as COVID-19.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121018997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determinants of the Number of Deaths from COVID-19: Differences between Low-Income and High-Income Countries in the Initial Stages of the Pandemic","authors":"Magali Valero, J. Valero-Gil","doi":"10.2139/ssrn.3617049","DOIUrl":"https://doi.org/10.2139/ssrn.3617049","url":null,"abstract":"PurposeThe purpose of this study is to understand the factors that contribute to the number of reported coronavirus (COVID-19) deaths among low-income and high-income countries, and to understand the sources of differences between these two groups of countries.Design/methodology/approachMultiple linear regression models evaluate the socio-economic factors that determine COVID-19 deaths in the two groups of countries. The Oaxaca–Blinder decomposition is used to examine sources of differences between these two groups.FindingsLow-income countries report a significantly lower average number of COVID-19 deaths compared to high-income countries. Community mobility and the easiness of carrying the virus from one place to another are significant factors affecting the number of deaths, while life expectancy is only significant in high-income countries. Higher health expenditure is associated with more reported deaths in both high- and low-income countries. Factors such as the transport infrastructure system, life expectancy and the percent of expenditure on health lead to the differences in the number of deaths between high- and low-income countries.Social implicationsOur study shows that mobility measures taken by individuals to limit the spread of the virus are important to prevent deaths in both high- and low-income countries. Additionally, our results suggest that countries with weak health institutions underestimate the number of deaths from COVID-19, especially low-income countries. The underestimation of COVID-19 deaths could be affecting a great number of people in poverty in low-income economies.Originality/valueThis paper contributes to the emerging literature on COVID-19 and its relation to socio-economic factors by examining the differences in reported between deaths between rates in low-income and high-income countries.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129053365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel Corona Virus (COVID-19) Pandemic: The Overall Scenario and its Effect on ECO","authors":"Vikram P. Bhalekar","doi":"10.2139/ssrn.3576168","DOIUrl":"https://doi.org/10.2139/ssrn.3576168","url":null,"abstract":"The world is suffering from a small species of diameter 65-125 nm and length of about 26-32kbs. A virus which was initially named as SARS-CoV-2 belongs to beta corona virus group. Later on it is named as novel corona virus (2019-nCov) or COVID-19. The world health organization declared it as a Pandemic on 11 March, 2020. This is biggest man made disaster, which could be stopped in the initial stage but now it has taken 21% lives of the total closed cases, this toll certainly advances to more than 30% worldwide. The death tolls of COVID-19 are very large as compared to combination of previous SARS and MARS, Ebola and all other viruses. At the current scenario China is recovering but it locked down the rest of the world. The virus which is originated from China now spreads in more than 200 countries and two international conveyances. In the current article the world’s perspective, origin, symptoms, medication, transmission and its effect on worlds ECO (-nomy, -logy, -tourism, -politics, -terrorism) is discussed.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126612806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Funding the Development and Manufacturing of COVID-19 Vaccines","authors":"G. Yamey, M. Schäferhoff, M. Pate, M. Chawla, K. Ranson, R. Hatchett, R. Wilder","doi":"10.2139/ssrn.3575660","DOIUrl":"https://doi.org/10.2139/ssrn.3575660","url":null,"abstract":"The SARS-CoV-2 virus, which causes COVID-19, has quickly spread worldwide. On January 30, 2020, the WHO declared COVID-19 to be a Public Health Emergency of International Concern and advised all governments to prepare for transmission in their countries. On March 11, 2020, the WHO declared that it had become a pandemic. There is uncertainty about what will happen next, e.g., the pandemic could involve multiple simultaneous epidemics of COVID-19 over 1-3 years, and/or SARS-CoV-2 could become a globally endemic virus. In this paper, we begin by arguing that the rapid development and scale-up of COVID-19 vaccines has become critical to reducing the morbidity, mortality, and economic damage associated with a pandemic. We show that new funding for COVID-19 vaccine development is required for all development stages and we estimate how much funding is needed. We examine ways to mobilize such funding and explore potential funding vehicles, including CEPI, the Coalition for Epidemic Preparedness Innovations, as well as the governance of such vehicles. Finally, we highlight issues such as vaccine manufacturing, intellectual property, global access, regulatory approval, and ethical and trial design considerations in conducting trials in the midst of the COVID-19 outbreak.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132428592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Making sense of the Global Coronavirus Data: The role of testing rates in understanding the pandemic and our exit strategy","authors":"R. Potluri, D. Lavu","doi":"10.2139/ssrn.3570304","DOIUrl":"https://doi.org/10.2139/ssrn.3570304","url":null,"abstract":"The Coronavirus disease 2019(COVID-19) outbreak has caused havoc across the world. Subsequently, research on COVID-19 has focused on number of cases and deaths and predicted projections have focused on these parameters. We propose that the number of tests performed is a very important denominator in understanding the COVID-19 data. We analysed the number of diagnostic tests performed in proportion to the number of cases and subsequently deaths across different countries and projected pandemic outcomes. We obtained real time COVID-19 data from the reference website Worldometer at 0900 BST on Saturday 4th April, 2020 and collated the information obtained on the top 50 countries with the highest number of COVID 19 cases. We analysed this data according to the number of tests performed as the main denominator. Country wise population level pandemic projections were extrapolated utilising three models - 1) inherent case per test and death per test rates at the time of obtaining the data (4/4/2020 0900 BST) for each country; 2) rates adjusted according to the countries who conducted at least 100000 tests and 3) rates adjusted according to South Korea. We showed that testing rates impact on the number of cases and deaths and ultimately on future projections for the pandemic across different countries. We found that countries with the highest testing rates per population have the lowest death rates and give us an early indication of an eventual COVID-19 mortality rate. It is only by continued testing on a large scale that will enable us to know if the increasing number of patients who are seriously unwell in hospitals across the world are the tip of the iceberg or not. Accordingly, obtaining this information through a rapid increase in testing globally is the only way which will enable us to exit the COVID-19 pandemic and reduce economic and social instability.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115840276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiological characteristics of an outbreak of Coronavirus Disease 2019 in the Philippines","authors":"M. Alipio, Joseph Dave Mendoza Pregoner","doi":"10.2139/ssrn.3568934","DOIUrl":"https://doi.org/10.2139/ssrn.3568934","url":null,"abstract":"The outbreak of Coronavirus disease 2019 (Covid-2019) is a source of great concern in the Philippines. In this paper, we described the epidemiological characteristics of the laboratory-confirmed patients with Covid-2019 in the Philippines as of April 3, 2020 and provided recommendations on how to limit the spread of the disease. Data from the DOH NCOV tracker and University of the Philippines Covid-2019 tracker were extracted, from its initiation (January 30, 2020) until the most recent situation report (April 3, 2020). The total number of cases and deaths were stratified by sex, age, and region of the Philippines. Descriptive statistics were used to analyze the demographic profile of the confirmed cases. Case fatality rate, in percent, was calculated by dividing the total number of deaths to the total number of confirmed cases. Results revealed that a total of 3,018 cases of Covid-2019 spread were confirmed across 17 regions in the Philippines. These cases occurred over the course of 73 days through person-to-person transmission, highlighting an extremely high infectivity rate. The 144 deaths accounted for, equate to 4.51 case fatality rate, seemingly lower compared to its predecessors, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), but higher compared to that of United States of America, Germany, mainland China, and neighboring Southeast Asian countries such as Malaysia, Singapore, Brunei, and Thailand. Of the 3,018 confirmed cases, majority were male, elderly, and diagnosed in Metro Manila region. Case fatality rates were higher in male and highest among elderly and Filipinos in the Ilocos region. With the surge on the number of cases, precautionary measures should remain a responsibility, and protocols for prevention need to be set. Adherence to infection control guidelines such as but not limited to frequently handwashing for at least 20 seconds, observing coughing etiquette, wearing of masks, and social distancing should be maintained in order to contain the disease.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133166070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiology and Clinical Characteristics of 50 Death Cases with COVID-2019 in the Philippines: A Retrospective Review","authors":"M. Alipio","doi":"10.2139/ssrn.3570612","DOIUrl":"https://doi.org/10.2139/ssrn.3570612","url":null,"abstract":"In an attempt to provide extensive information pertaining to the epidemiological and clinical characteristics of death cases with COVID-2019 in the Philippines, this retrospective study was conducted using data of 50 death cases from January 30 to April 3, 2020. The patients’ information including demographic profile (age, sex, nationality, residence), date of confirmation for positive COVID-2019 case, date of death, travel/exposure history, cause of death, and comorbidities were taken from open-access COVID-2019 databases of the Department of Health and University of the Philippines. Results revealed that the mean age of death cases was 68.48 ± 10.40 years, males outnumbered females in terms of mortality, most of the death cases were observed in the age group 70 – 79, and almost all of the cases were Filipino residing in Quezon City and Manila. Patients with no travel history or no exposure to a known COVID-2019 case are susceptible to death. Majority of the cases died because of underlying diseases, the most common of which was hypertension, followed by diabetes mellitus, chronic kidney disease, acute kidney injury, asthma, and kidney disease. Mean number of comorbidities among the death cases was 2.12 ± 1.04. All patients died because of respiratory failure. Most of the death cases died before the release of COVID-2019 positive test result. A proportion of cases died on the same day the COVID-2019 positive test result was released. The elderly individuals are more susceptible to mortality. The underlying diseases (e.g., hypertension, diabetes mellitus, chronic kidney disease) exacerbated the risks of death among the sampled cases. Patients with no travel history or no exposure to a known COVID-2019 case are vulnerable to death suggesting a sustained community transmission of infection in the Philippines. The findings of the study provide important implications to the government health officials and local government units of the Philippines. The provision and capacitation of laboratory testing to the local government units may be undertaken to increase testing of suspected individuals, which may ultimately reduce cases of mortality. Mean time difference (difference between time of death and time positive test result was released) was – 0.68 indicating that an average patient in the sample died before positive test result was released. This is quite saddening as most of the death cases were not informed of the positive test result ahead of time before dying. More testing facilities, including kits, should be provided to mitigate this problem.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125076827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Basic Model for the Pandemic and Its Extensions","authors":"A. Odetti, V. Piterbarg","doi":"10.2139/ssrn.3568156","DOIUrl":"https://doi.org/10.2139/ssrn.3568156","url":null,"abstract":"We describe and briefly examine the standard model for viral infection, the so-called SIR model, and its potential usage in the current situation. We furthermore extend the model to account for government interventions, and for differences in testing approaches in different countries.","PeriodicalId":430418,"journal":{"name":"Infectious Diseases eJournal","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132178226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}