TY - JOUR
T1 - Early epidemiological indicators, outcomes, and interventions of COVID-19 pandemic
T2 - A systematic review
AU - Patel, Urvish
AU - Malik, Preeti
AU - Mehta, Deep
AU - Shah, Dhaivat
AU - Kelkar, Raveena
AU - Pinto, Candida
AU - Suprun, Maria
AU - Dhamoon, Mandip
AU - Hennig, Nils
AU - Sacks, Henry
N1 - Funding Information:
Funding: The study had no internal or external funding source. Maria Suprun is funded by the Integrated Pharmacological Sciences training program grant from the National Institute of General Medical Sciences (NIGMS, T32G-MO62754).
Funding Information:
Informed consent: The data used in this study are publicly available and de-identified database thus informed consent or IRB approval was not needed for this study. Funding: The study had no internal or external funding source. Maria Suprun is funded by the Integrated Pharmacological Sciences training program grant from the National Institute of General Medical Sciences (NIGMS, T32GMO62754). Authorship contributors: UP conceived of the idea. PM and CP reviewed the literature and collected the data with the help of UP and DM. UP and PM performed biostatistical analysis. UP, PM, DM, DS, and RK formulated the tables and graphs. UP, PM, DM, DS, RK, CP, and MS wrote the main draft of the manuscript with support of MD, NH, and HS. HS supervised the project. Conflicts of interest: The authors completed the ICMJE Unified Competing Interest form (available upon request from the corresponding author), and declare no conflicts of interest. Additional material Online Supplementary Document
PY - 2020/12
Y1 - 2020/12
N2 - Background Coronavirus disease-2019 (COVID-19), a pandemic that brought the whole world to a standstill, has led to financial and health care burden. We aimed to evaluate epidemiological characteristics, needs of resources, outcomes, and global burden of the disease. Methods Systematic review was performed searching PubMed from December 1, 2019, to March 25, 2020, for full-text observational studies that described epidemiological characteristics, following MOOSE protocol. Global data were collected from the JHU-Corona Virus Resource Center, WHO-COVID-2019 situation reports, KFF.org, and Worldometers.info until March 31, 2020. The prevalence percentages were calculated. The global data were plotted in excel to calculate case fatality rate (CFR), predicted CFR, COVID-19 specific mortality rate, and doubling time for cases and deaths. CFR was predicted using Pearson correlation, regression models, and coefficient of determination. Results From 21 studies of 2747 patients, 8.4% of patients died, 20.4% recovered, 15.4% were admitted to ICU and 14.9% required ventilation. COVID-19 was more prevalent in patients with hypertension (19.3%), smoking (11.3%), diabetes mellitus (10%), and cardiovascular diseases (7.4%). Common complications were pneumonia (82%), cardiac complications (26.4%), acute respiratory distress syndrome (15.7%), secondary infection (11.2%), and septic shock (4.3%). Though CFR and COVID-19 specific death rates are dynamic, they were consistently high for Italy, Spain, and Iran. Polynomial growth models were best fit for all countries for predicting CFR. Though many interventions have been implemented, stern measures like nationwide lockdown and school closure occurred after very high infection rates (>10cases per 100 000population) prevailed. Given the trend of government measures and decline of new cases in China and South Korea, most countries will reach the peak between April 1-20, if interventions are followed. Conclusions A collective approach undertaken by a responsible government, wise strategy implementation and a receptive population may help contain the spread of COVID-19 outbreak. Close monitoring of predictive models of such indicators in the highly affected countries would help to evaluate the potential fatality if the second wave of pandemic occurs. The future studies should be focused on identifying accurate indicators to mitigate the effect of underestimation or overestimation of COVID-19 burden.
AB - Background Coronavirus disease-2019 (COVID-19), a pandemic that brought the whole world to a standstill, has led to financial and health care burden. We aimed to evaluate epidemiological characteristics, needs of resources, outcomes, and global burden of the disease. Methods Systematic review was performed searching PubMed from December 1, 2019, to March 25, 2020, for full-text observational studies that described epidemiological characteristics, following MOOSE protocol. Global data were collected from the JHU-Corona Virus Resource Center, WHO-COVID-2019 situation reports, KFF.org, and Worldometers.info until March 31, 2020. The prevalence percentages were calculated. The global data were plotted in excel to calculate case fatality rate (CFR), predicted CFR, COVID-19 specific mortality rate, and doubling time for cases and deaths. CFR was predicted using Pearson correlation, regression models, and coefficient of determination. Results From 21 studies of 2747 patients, 8.4% of patients died, 20.4% recovered, 15.4% were admitted to ICU and 14.9% required ventilation. COVID-19 was more prevalent in patients with hypertension (19.3%), smoking (11.3%), diabetes mellitus (10%), and cardiovascular diseases (7.4%). Common complications were pneumonia (82%), cardiac complications (26.4%), acute respiratory distress syndrome (15.7%), secondary infection (11.2%), and septic shock (4.3%). Though CFR and COVID-19 specific death rates are dynamic, they were consistently high for Italy, Spain, and Iran. Polynomial growth models were best fit for all countries for predicting CFR. Though many interventions have been implemented, stern measures like nationwide lockdown and school closure occurred after very high infection rates (>10cases per 100 000population) prevailed. Given the trend of government measures and decline of new cases in China and South Korea, most countries will reach the peak between April 1-20, if interventions are followed. Conclusions A collective approach undertaken by a responsible government, wise strategy implementation and a receptive population may help contain the spread of COVID-19 outbreak. Close monitoring of predictive models of such indicators in the highly affected countries would help to evaluate the potential fatality if the second wave of pandemic occurs. The future studies should be focused on identifying accurate indicators to mitigate the effect of underestimation or overestimation of COVID-19 burden.
UR - http://www.scopus.com/inward/record.url?scp=85121161256&partnerID=8YFLogxK
U2 - 10.17711/sm.0185-3325.2020.010
DO - 10.17711/sm.0185-3325.2020.010
M3 - Article
AN - SCOPUS:85121161256
SN - 2047-2978
VL - 10
SP - 65
EP - 71
JO - Journal of Global Health
JF - Journal of Global Health
IS - 2
ER -