scholarly journals Factors influencing COVID-19 case burden and fatality rates findings from secondary data analysis of major urban agglomerations in India

2020 ◽  
Vol 7 (8) ◽  
pp. 3284
Author(s):  
Deodatt M. Suryawanshi ◽  
Raghuram Venugopal ◽  
Ramchandra Goyal
Keyword(s):  
Data Analysis ◽  
Negative Correlation ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Secondary Data ◽  
Health Financing ◽  
Secondary Data Analysis ◽  
Fatality Rate ◽  
Health Index ◽  
Significant Difference

In December 2019, SARS COV-2 which originated in the Chinese city of Wuhan achieved pandemic proportions and spread rapidly to countries through International air traffic causing acute respiratory infection and deaths. Presence of International airports, demography, health financing and human developments factors were assumed to influence COVID-19 cases burden and case fatality rate (CFR). So, this study was undertaken to find a association between these factors and COVID-19 cases and deaths. The study used 48 districts using purposive sampling as proxy for cities and used secondary data analysis. Data was obtained for various variables like demographic, Health Financing, Indices and Testing infrastructure, COVID cases burden and case fatality from trusted sources. Descriptive statistics correlational statistics using Pearsons coefficient students T was used to describe, correlate and find significant difference in the data. The analysis found a significant difference between COVID cases burden in districts with International Airports (p<0.039) and those without it. Positive correlation of population density (r=0.65) with COVID-19 case burden and negative correlation of case fatality rate with NITI Aayogs health index (r=-0.12), human development index (HDI) (r=-0.18), per-capita expenditure on health (r=-0.072) and a correlation of r=0.16 was observed for gross state domestic product. Decongestion of cities through perspective urban planning is the need of the hour. Stricter quarantine measures in those districts with international airports can help reduce the transmission. Negative correlation of HDI and NITI Aayogs health index with CFR emphasizes the importance of improvements in social determinants of health.

Phylogenetic group and serotype of E. coli isolates are important risk factors affecting intensity of colibacillosis in broilers

2018 ◽  
Author(s):  
S. Kumar ◽  
R. Gupta ◽  
N. Jindal and Y.C. Bangar
Keyword(s):  
Case Fatality Rate ◽  
Age Groups ◽  
Case Fatality ◽  
Phylogenetic Group ◽  
Fatality Rate ◽  
Phylogenetic Groups ◽  
Factors Affecting ◽  
E Coli ◽  
Significant Difference ◽  
Class 1

The study was conducted on 106 E. coli isolates to determine the phylogenetic group, serotype and carriage of Class 1 integrons in isolates and ascertain their association along with other parameters with vital disease measures in broiler flocks affected with colibacillosis. Out of 32 isolates of which “O” antigen was characterized, serogroup O2 comprising of 12 (37.5%) isolates was most prevalent in the present study. Most of the isolates (85/106; 80.19%) belonged to phylogenetic group B2. Mean apparent morbidity, mortality and case fatality rate (CFR) were 3.77%, 2.32% and 61.49%, respectively. There was significant difference in number of outbreaks reported in different age groups (p less than 0.0001). Also, there was significant association between phylogenetic group and age of outbreak due to E. coli (p=0.024). Comparatively, no significant association was observed between age of outbreaks and serotypes (p=0.980). There was significant association between various disease measures and E. coli isolates affiliated to various phylogenetic groups and serotypes. All the measures (apparent morbidity, mortality and CFR) of disease were highest in outbreaks due to isolates of phylogenetic group B2 and serogroup O20. However, the measures were not significantly affected by the presence of integrons in the E. coli.

scholarly journals Covid-19 High Attack Rate Can Lead to High Case Fatality Rate

2021 ◽  
Author(s):  
Tareef Fadhil Raham
Keyword(s):  
Mortality Rate ◽  
Attack Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Positive Influence ◽  
P Value ◽  
Fatality Rate ◽  
Mean Values ◽  
Paired Samples ◽  
Significant Difference

Background: During the current Covid-19 pandemic case fatality rate (CFR) estimates were subjected to a lot of debates regarding the accuracy of its estimations, predictions, and the reason of across countries variances. In this context, we conduct this study to see the relationship between attack rate (AR) and CFR. The study hypothesis is based on two: 1- evidence suggests that the mortality rate (MR) has a positive influence on case fatality ratio (CFR), 2- and increase number of Covid-19 cases leads to increased mortality rate (MR). Material and methods: Thirty countries and territories were chosen. Inclusion criterion was > 500 Covid-19 reported cases per 10,000 population inhabitants. Data on covid-19 cases and deaths was selected as it was on March 10, 2021. Statistical methods used are descriptive and one-sample Kolmogorov-Smirnov (K-S), the one-way ANOVA, Levene, least significant different (LSD), and matched paired-samples T-tests. Results: ANOVA test showed a significant difference at P<0.01 among all studied groups concerning AR and CFR mean values. Group of countries with MR ≥ 15 death / 104 inhabitants recorded the highest level of crude mean CFR and AR values, and recorded the highest gap with leftover groups, especially with countries reported MR of <10 death/ 104 inhabitants. There were independence 95% confidence intervals of mean CFR and AR values between countries with ≥ 15 death / 104 MR and countries with MR of <10 death /104. There was a significant difference between countries with MR ≥ 15 death / 104 inhabitants and countries with MR of <10 death / 10 4 inhabitants groups through least significant difference (LSD) test for CFR%( 0.042 p-values) and Games Howell (GH) test for AR/104 (p-value 0.000). Conclusions: CFR has a positive significant association with AR.

scholarly journals Morbidity, mortality and case fatality rate from chronic hepatitis B with and without a delta agent in Kyrgyzstan for the period 2010–2017

2020 ◽  
Vol 1 (10) ◽  
pp. 39-44
Author(s):  
K. A. Nogoibaeva ◽  
S. T. Tobokalova ◽  
K. T. Kasymbekova ◽  
S. I. Umarova
Keyword(s):  
Hepatitis B ◽  
Viral Hepatitis ◽  
Case Fatality Rate ◽  
Age Groups ◽  
Case Fatality ◽  
Chronic Viral Hepatitis ◽  
Fatality Rate ◽  
Significant Difference ◽  
Viral Hepatitis B ◽  
Microsoft Office

The purpose of the study is to research the morbidity, mortality and case fatality rate y of chronic viral hepatitis B without and with a delta agent from 2010–2017. in Kyrgyzstan.Materials and methods: analyzed state reporting forms No. 12 “Report on morbidity and preventive work (family medicine center, dispensary)” and “C51 — Distribution of deaths by sex, age groups and causes of death” from 2010–2017. Data processed by Microsoft Office Excel.Results: In the country from 2010–2017 3292 cases of chronic viral hepatitis B were detected, 1738 patients of them verified an independent course (СhHBV), and 1,554 patients combined with a delta agent (СhHDV), while the incidence did not have a statistically significant difference (3.80/0000, 95% CI 2.4–4.0 and 3.40/0000, 95% CI 2.2–3.4, СhHBV and СhHDV, respectively) were 20 times lower compared to the HBV Carrier (60 40/0000). There was no statistically significant difference between the cumulative morbidity, mortality, case fatality rate and the proportion of deaths in СhHBV and СhHDV. The death rate СhHBV increased by 4.7 times (0.090/0000 and 0.410/0000), case fatality rate — by 11.8 times (1355.00/0000 and 16025.60/0000) amid a decrease the incidence is 2.5 times (6.40/0000 and 2.50/0000) from 2014 to 2017, respectively. At СhHDV, the mortality rate was also increased by 4.7 times (0.030/0000 and 0.160/0000), case fatality rate — by 32.3 times (793.70/0000 and 25641.80/0000) against the background of a decrease in incidence by 6.9 times (4.40/0000 and 0.60/0000) from 2014 to 2017, respectively.Conclusion: In Kyrgyzstan from 2010–2017, relatively low detectability of chronic forms of HBV infection with and without delta agent was found, compared with the “HBV carrier”. There has been an increase in mortality and case fatality rate over the past 4 years, with a sharp rise in 2017 against the background of a downward trend in the incidence of СhHBV and СhHDV.

scholarly journals Geo-temporal distribution of 1,688 Chinese healthcare workers infected with COVID-19 in severe conditions – a secondary data analysis

2020 ◽  
Author(s):  
Wayne Gao ◽  
Mattia Sanna ◽  
Chi Pang Wen
Keyword(s):  
Disease Severity ◽  
Healthcare Workers ◽  
Case Fatality ◽  
Temporal Distribution ◽  
Secondary Data ◽  
Accurate Estimation ◽  
Fatality Rate ◽  
Quality Healthcare ◽  
Short Period ◽  
Significant Difference

IntroductionThe COVID-19 outbreak is posing an unprecedented challenge to healthcare workers. This study analyzes the geo-temporal effects on disease severity for the 1,688 Chinese healthcare workers infected with COVID-19.MethodUsing the descriptive results recently reported by the Chinese CDC, we compare the percentage of infected healthcare workers in severe conditions over time and across three areas in China, and the fatality rate of infected healthcare workers with all the infected individuals in China aged 22-59 years.ResultsAmong the infected Chinese healthcare workers whose symptoms onset appeared during the same ten-day period, the percentage of those in severe conditions decreased statistical significantly from 19.7% (Jan 11 – 20) to 14.4% (Jan 21 – 31) to 8.7% (Feb 1 – 11). Across the country, there was also a significant difference in the disease severity among patients symptoms onset during the same period, with Wuhan being the most severe (17%), followed by Hubei Province (10.4%), and the rest of China (7.0%). The case fatality rate for the 1,688 infected Chinese healthcare workers was significantly lower than that for the 29,798 infected patients aged 20-59 years—0.3% (5/1,688) vs. 0.65% (193/29,798), respectively.ConclusionThe disease severity improved considerably over a short period of time in China. The more severe conditions in Wuhan compared to the rest of the country may be attributable to the draconian lockdown. The clinical outcomes of infected Chinese healthcare workers may represent a more accurate estimation of the severity of COVID-19 for those who have access to quality healthcare.

scholarly journals Burden and Trend of Measles in Nigeria: Five-year Review Case-base Surveillance Data

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Ibrahim S. Baffa ◽  
Yahaya Mohammed ◽  
Rabi Usman ◽  
Aisha Abubakar ◽  
Patrick Nguku
Keyword(s):  
Disease Surveillance ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Secondary Data ◽  
Epidemiological Data ◽  
Laboratory Diagnosis ◽  
Northern Region ◽  
World Health ◽  
Fatality Rate ◽  
Health Organization

ObjectiveWe reviewed measles specific Integretaged Disease Surveillance and Response (IDSR) data from Nigeria over a five-year period to highlights its burden and trends, and make recommendations for improvements.IntroductionMeasles is a vaccine preventable, highly transmissible viral infection that affects mostly under-five year children. The disease is caused by a Morbillivirus; member of the Paramyxovirus family.MethodsWe conducted a secondary data analysis of measles specific IDSR records of all States in Nigeria from January 2012 to September 2016. The record had reported measles cases with laboratory outcomes from all the States. IDSR weekly epidemiological data were obtained from Surveillance Unit, Nigerian Centre for Disease Control (NCDC).ResultsA total of 131,732 cases were recorded within the period. Highest number of cases 57,892(43.95%) were recorded in 2013 while the least number of cases 11,061(8.4%) were recorded in 2012. A total of 817 deaths were recorded, given a case fatality rate (CFR) of 0.62%. The CFR showed a decreasing trend over the years with the highest CFR (1.43%) recorded in 2012 and the least CFR (0.44%) recorded in 2016. Only 8,916 (6.7%) cases were confirmed by laboratory investigation. The Northwest region recorded the highest attack rate (AR) of 149.7 cases per 100,000 population, followed by the Northeast region with 140.2 cases per 100,000 population, while the South-south region recorded the least AR of 15.8 cases per 100,000 population. Case Fatality Rate per region followed similar pattern, with the Northcentral region having the highest CFR of 4.38%. The trend of measles cases followed the same pattern. Cases peaked at March, then gradually reduced to lowest level at June.ConclusionsMeasles infection remains a burden especially in the northern region of Nigeria. Though measles fatalities were on decline over the years, laboratory diagnosis of cases has been suboptimal. We recommended improvement on routine immunization and measles case management, and strengthening of regional laboratories capacity for measles diagnosis.References1. WHO | Measles. WHO [Internet]. World Health Organization; 2017 [cited 2017 Apr 10]; Available from: http://www.who.int/mediacentre/factsheets/fs286/en/2. Akande TM. A review of measles vaccine failure in developing countries. Niger. Med. Pract. SAME Ventures; 2007;52:112–6.3. Ibrahim BS, Gana GJ, Mohammed Y, Bajoga UA, Olufemi AA, Umar AS, et al. Outbreak of measles in Sokoto State North-Western Nigeria, three months after a supplementary immunization campaign: An investigation report 2016. Australas. Med. J. AUSTRALASIAN MEDICAL JOURNAL PTY LTD HILLARYS, GPO BOX 367, PERTH, WA 6923, AUSTRALIA; 2016;9:324–35. 

scholarly journals Analysis of Covid - 19 Situations in Davanagere District, Karnataka

2021 ◽  
Vol 2 (4) ◽  
pp. 01-08
Author(s):  
Gouri Sakre ◽  
Gulappa Devagappanavar
Keyword(s):  
Attack Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Secondary Data ◽  
World Health ◽  
Severe Illness ◽  
Fatality Rate ◽  
First Case ◽  
Increased Risk ◽  
Novel Coronavirus

Background: According to CDC, Coronavirus disease 2019 (COVID-19) is caused by a new coronavirus which was first identified in Wuhan, China, in December 2019. Although most people who have COVID-19 have mild symptoms, it can also cause severe illness and even death. Some groups, including older adults and people who have certain underlying medical conditions, are at increased risk of severe illness. On February 11, 2020, the World Health Organization announced an official name for the disease that is causing the 2019 novel coronavirus outbreak. The new name of this disease is coronavirus disease 2019, abbreviated as COVID-19. Objectives: Analysis of COVID 19 data in the Davanagere district from April 2020 to August 2020. Methods: In this current study the secondary data is obtained from the Official Website of Government of Karnataka, Covid-19 Informational Portal – Media Bulletin. By using different indicators Davanagere district covid data is further used to calculate Attack rate, Case fatality rate and complete case fatality rate. Results: In this study it is found that, in the month of April there were no covid positive cases reported till fourth week of month, by fourth week, total two positive cases were reported the first case being encountered on 28th April 2020, with discharge of those patient in the end of the month. The attack rate has steeped up from 8.018 to 355.74 per one lakh population i.e. about 44 times more than initial months of pandemic. The strict preventive measures were followed by public and government too. So the prevalence rate is less in May, June and went on increasing once the unlocking is done. In summer the total positive cases steeping up from 2 cases to 154 total positive cases for the month April to May, and there is steady in rise of total positive cases for the month June with total positive cases of 153. In the beginning of summer there were fewer cases as pandemic was just begun and chances of transmission were very less. As monsoon appeared in June last week there is surge in total positive cases. With added burden of Unlock 1.0 phase, as public started moving out from home without any freak of infection. Conclusion: In this study it is found that due to strict nationwide lockdown and social distancing, hygiene practices among the Davanagere people has made it possible to restrict the spread of covid among the people, although the international immigration of Davanagere residents lead to transmission of infection. Further removal of lockdown after three months has lead to three fold spread of disease. Also there is rise in death rate, attack rate and case fatality in Davanagere district.

scholarly journals Standardization and Age-Distribution of COVID-19: Implications for Variability in Case Fatality and Outbreak Identification

2020 ◽  
Author(s):  
David N. Fisman ◽  
Amy L. Greer ◽  
Ashleigh R. Tuite
Keyword(s):  
Data Analysis ◽  
Early Stage ◽  
Age Distribution ◽  
Case Fatality ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Apparent Size ◽  
Older Individuals ◽  
Indirect Standardization ◽  
The Impact

AbstractBackgroundEpidemiological data from the COVID-19 pandemic has demonstrated variability in attack rates by age, and country-to-country variability in case fatality ratio (CFR).ObjectiveTo use direct and indirect standardization for insights into the impact of age-specific under-reporting on between-country variability in CFR, and apparent size of COVID-19 epidemics.DesignPost-hoc secondary data analysis (“case studies”), and mathematical modeling.SettingChina, global.InterventionsNone.MeasurementsData were extracted from a sentinel epidemiological study by the Chinese Center for Disease Control (CCDC) that describes attack rates and CFR for COVID-19 in China prior to February 12, 2020. Standardized morbidity ratios (SMR) were used to impute missing cases and adjust CFR. Age-specific attack rates and CFR were applied to different countries with differing age structures (Italy, Japan, Indonesia, and Egypt), in order to generate estimates for CFR, apparent epidemic size, and time to outbreak recognition for identical age-specific attack rates.ResultsSMR demonstrated that 50-70% of cases were likely missed during the Chinese epidemic. Adjustment for under-recognition of younger cases decreased CFR from 2.4% to 0.8% (assuming 50% case ascertainment in older individuals). Standardizing the Chinese epidemic to countries with older populations (Italy, and Japan) resulted in larger apparent epidemic sizes, higher CFR and earlier outbreak recognition. The opposite effect was demonstrated for countries with younger populations (Indonesia, and Egypt).LimitationsSecondary data analysis based on a single country at an early stage of the COVID-19 pandemic, with no attempt to incorporate second order effects (ICU saturation) on CFR.ConclusionDirect and indirect standardization are simple tools that provide key insights into between-country variation in the apparent size and severity of COVID-19 epidemics.FundingThe research was supported by a grant to DNF from the Canadian Institutes for Health Research (2019 COVID-19 rapid researching funding OV4-170360).

The Predictive Relationship of Pediatric Body Mass Indexes and Comorbid Diagnoses

2012 ◽  
Vol 4 (5) ◽  
pp. 283-288
Author(s):  
Jessica Parrott ◽  
Carolyn Rutledge ◽  
Kathie Zimbro ◽  
Laurel Shepherd
Keyword(s):  
Data Analysis ◽  
Children And Adolescents ◽  
Body Mass ◽  
Pediatric Obesity ◽  
Secondary Data ◽  
Original Data ◽  
Secondary Data Analysis ◽  
Health Care Environment ◽  
Health Services Use ◽  
Significant Difference

Pediatric obesity is a leading threat to the long-term health of the population. The rise in pediatric obesity has resulted in increased comorbidities and decreased health status. A secondary data analysis was completed to evaluate the relationship between body mass index (BMI), health care environment, and health services use of pediatric patients. This research used a retrospective secondary data analysis of 942 charts of which 526 contained critical data elements. The information was gathered by means of an original data collection tool. Statistical analysis was achieved through χ2 and ANOVA techniques. The project was congruent with the then current Healthy People 2010 goals of improving health, fitness, and quality of life through daily physical activity for children and adolescents and also aimed to reduce the proportion of children and adolescents who are overweight or obese. There was a statistically significant difference between BMI levels and comorbid diagnoses ( χ2, P = .035) with an increase among obese levels, particularly with abscesses (ANOVA, P = .003). It was found that pediatric obesity results in increased comorbidities, most significantly abscesses.

A Short-Term Forecast Scenario for COVID-19 Epidemic and Allocated Hospital Readiness in Egypt (Preprint)

2020 ◽  
Author(s):  
Engy ElGhitany
Keyword(s):  
Exponential Growth ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Secondary Data ◽  
Fatality Rate ◽  
Short Term ◽  
Short Term Forecast ◽  
Epidemic Curve ◽  
Preparedness Planning ◽  
Term Forecast

BACKGROUND The novel virus COVID-19, also known as SARS-CoV 2, is currently rapidly spreading around the globe and pushing healthcare systems to the limits of their capacity. One of the functions of predictive models is to timely act for epidemic preparedness including hospital preparedness. In Egypt, like many other countries in the world, the epidemic situation and forecasting have not yet sufficiently studied. OBJECTIVE The study was carried out to develop a short-term forecast scenario for the COVID-19 epidemic situation in Egypt and predict the hospital needs to accommodate the growing number of cases. METHODS Secondary data from the COVID-2019 daily reports and the report issued 8th of April by the Egyptian Ministry of Health and Population were used. Due to the daily changing level of knowledge and data, the article reflects the status up to 18 April 2020. The prediction was based on the exponential growth rate model. For the depiction of the situation, the full length of the epidemic timeline was analyzed (from February 14th till April 18th). The growth rates and their rates of decline during the period from the 22nd of March till the 18th of April were calculated and extrapolated in the coming 7 weeks. The predicted hospital needs were assessed against the announced allocated resources. RESULTS The epidemic curve in Egypt is on the ascending arm as of April, 18. The active cases showed exponential growth from the start of the epidemic till April, 18. At the end of this period time, the recovery rate was 23.12% and the case fatality rate (CFR) was7.39. The case fatality rate median level during the last four weeks was 6.64. The active cases are expected to reach more than 20,000 by late May then starts to decline. The allocated regular hospital beds are predicted to show shortage by the time of the release of the paper. The intensive care units (ICU) beds and ventilators are predicted to show insufficiency on May 6. CONCLUSIONS The COVID-19 epidemic in Egypt is expected to continue on the rise for the next few weeks and expected to start to decline late in May, 2020. Our estimates should be useful in preparedness planning. Serious actions should be taken to provide ICU beds and ventilators enough for the predicted number of cases that would need them, not later than the end of April. Mitigation actions have to continue for the coming 6 weeks or until the epidemic situation is more clearly seen.

scholarly journals 444. County-level COVID-19 Case Fatality Rate in Medicaid Expansion States Compared to Non-Expansion States

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S323-S324
Author(s):  
Walid El-Nahal ◽  
Stephen Berry ◽  
Kevin Psoter ◽  
Kelly Gebo
Keyword(s):  
Case Fatality Rate ◽  
Negative Binomial ◽  
District Of Columbia ◽  
Case Fatality ◽  
County Level ◽  
Medicaid Expansion ◽  
Fatality Rate ◽  
Physician Density ◽  
Related Case ◽  
Significant Difference

Abstract Background Medicaid expansion has been adopted by 38 states and the District of Columbia,1,2 contributing to lower rates of uninsured individuals in the US.3 During the COVID-19 pandemic, Medicaid enrollment offset employer-based insurance losses precipitated by the recession.4 The aim of this study was to evaluate whether Medicaid expansion may have impacted COVID-19 mortality. Methods We conducted an ecologic study that included all US counties in the 50 states and District of Columbia. County-specific Medicaid expansion status was based on whether expansion was adopted within the state. COVID-19 cases and deaths for each county were obtained from the Centers of Disease Control (CDC). Unadjusted and multivariable negative binomial regression with robust standard errors to account for clustering of counties within each state were used to evaluate the association of COVID-19 case fatality rate and Medicaid expansion status. Adjusted models included the addition of four sets of county-level covariates thought to influence the association of Medicaid status and COVID-19 fatality rate: demographics, comorbidities, economic indicators, and physician density. These analyses were then performed in subgroups of counties defined by urbanicity (metro, suburban or rural) and quartiles of poverty rates. Incidence Rate Ratios (IRR) and 95% confidence intervals (CI) are reported. Results A total of 1,814 Medicaid expansion and 1,328 non-expansion counties were included in the analysis. Crude case fatality rates were 2.1% (non-expansion) and 1.8% (expansion). Medicaid expansion was not associated with a significantly lower COVID-19 case fatality rate in either the unadjusted (IRR: 0.86; 95% CI: 0.74, 1.01) or fully adjusted (IRR: 1.02; 95% CI: 0.90, 1.16) models. In adjusted models, Medicaid expansion status was also not associated with differences in COVID-19 case fatality rate when counties were stratified by either urbanicity or percent of individuals living below the poverty line. Conclusion In this county-level analysis, Medicaid expansion status was not associated with a significant difference in county-level COVID-19-related case fatality rates among people of all ages. Future individual-level studies are needed to better characterize the effect of Medicaid on COVID-19 mortality. Disclosures All Authors: No reported disclosures

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