scholarly journals Epidemiological philosophy of pandemics

Author(s):  
Tareef Fadhil Raham

Background: During  the COVID-19 pandemic, clinicians have struggled to understand why case fatality rates vary among countries. The role of clusters of infections in COVID-19 severity is well known before, furthermore the case overload was attributed to increased COVID-19 mortality in certain locations. The background theory in this study was the  already existing evidence that an increased viral load (density of infection) leads to more fatalities. The aim of this study was to find the correlation between high number of cases and high mortality (MR) in different countries and to find the correlation of MR with case fatality rate (CFR).Methods: We chose thirty-one countries with testing coverage levels of >400,0000 tests/M and populations greater than 1 million inhabitants. We used ANOVA regression analyses to test the associations.Results: There was a very highly significant correlation between MR and the total number of cases/million population inhabitants (M) (p=0.0000). The CRF changed with a change in the MR. A very high positive influence of the COVID-19 MR on the CFR (p= 0.0000).Conclusions: Increased number of cases per million inhabitants is associated with increased MR. Increased MR is associated with increased CFR. These findings explain variable mortality rates in relation to CFR and to the number of cases/M. This evidence gives us an idea of the behavior of epidemics in general. This  will help in the development of infection control policies.

2021 ◽  
Author(s):  
Tareef Fadhil Raham

Objectives: Currents estimates of total cases of COVID-19 are largely based on previously determined case fatality rates (CFR)s. The background theory in this study is based on two: There is no evidence that during epidemics CFR is fixed throughout time or place and there is evidence that viral load (dense of infection) leads to more fatalities. Study Design: This study was done to look for any relationship between mortality rate (MR) presented as deaths/ million (M) population with both of the total cases / (M) population (density of infection) and of CFR. We chose 31 countries with testing coverage > 400,0000 tests /M and with> 1 million population. Methods: We used ANOVA regression analyses for testing the associations. Results: CRF is not a fixed ratio as it changed with a change in (MR). The COVID-19 deaths / million data were fit to calculate the total cases through the equation: total deaths /M =0.006593 X (total cases to the power 1.016959) with a too highly significant correlation between total deaths / 1M and total cases (P-value 0.0000). There was a high positive influence of COVID-19 MR on the CFR (P-value = 0.0002) by non-linear regression (power model), through the equation: CFR = (0.093200) X (total deaths/ M.) to the power 0.366580 Conclusions: There is new evidence of using MR for estimation of CFR and total cases through uniform formulas applicable during this pandemic and possibly for every epidemic. This evidence gives us an understandable idea about epidemics' behavior.


2006 ◽  
Vol 46 (2) ◽  
pp. 230-235 ◽  
Author(s):  
Anna SkoczyÅ„ska ◽  
Marcin KadÅ‚ubowski ◽  
Józef Knap ◽  
Maria Szulc ◽  
Marzena Janusz-Jurczyk ◽  
...  

2020 ◽  
Author(s):  
Chen Wei ◽  
Chien-Chang Lee ◽  
Tzu-Chun Hsu ◽  
Wan-Ting Hsu ◽  
Chang-Chuan Chan ◽  
...  

ABSTRACTAlthough testing is widely regarded as critical to fighting the Covid-19 pandemic, what measure and level of testing best reflects successful infection control remains unresolved. Our aim was to compare the sensitivity of two testing metrics-population testing number and testing coverage-to population mortality outcomes and identify a benchmark for testing adequacy with respect to population mortality and capture of potential disease burden. This ecological study aggregated publicly available data through April 12 on testing and outcomes related to COVID-19 across 36 OECD (Organization for Economic Development) countries and Taiwan. All OECD countries and Taiwan were included in this population-based study as a proxy for countries with highly developed economic and healthcare infrastructure. Spearman correlation coefficients were calculated between the aforementioned metrics and following outcome measures: deaths per 1 million people, case fatality rate, and case proportion of critical illness. Fractional polynomials were used to generate scatter plots to model the relationship between the testing metrics and outcomes. Testing coverage, but not population testing number, was highly correlated with population mortality (rs= −0.79, P=5.975e-09 vs rs = − 0.3, P=0.05) and case fatality rate (rs= −0.67, P=9.067e-06 vs rs= −0.21, P=0.20). A testing coverage threshold of 15-45 signified adequate testing: below 15, testing coverage was associated with exponentially increasing population mortality, whereas above 45, increased testing did not yield significant incremental mortality benefit. Testing coverage was better than population testing number in explaining country performance and can be used as an early and sensitive indicator of testing adequacy and disease burden. This may be particularly useful as countries consider re-opening their economies.


2020 ◽  
Vol 10 (1) ◽  
pp. 1792620 ◽  
Author(s):  
Mohammad M. Hassan ◽  
Mohamed E. El Zowalaty ◽  
Shahneaz A. Khan ◽  
Ariful Islam ◽  
Md. Raihan K. Nayem ◽  
...  

BMC Urology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Héctor Gallegos ◽  
Pablo A. Rojas ◽  
Francisca Sepúlveda ◽  
Álvaro Zúñiga ◽  
Ignacio F. San Francisco

Abstract Objectives To establish the role of BCG instillations in the incidence and mortality of COVID-19. Patients and methods NMIBC patients in instillations with BCG (induction or maintenance) during 2019/2020 were included, establishing a COVID-19 group (with a diagnosis according to the national registry) and a control group (NO-COVID). The cumulative incidence (cases/total patients) and the case fatality rate (deaths/cases) were established, and compared with the national statistics for the same age group. T-test was used for continuous variables and Fisher's exact test for categorical variables. Results 175 patients were included. Eleven patients presented CIS (11/175, 6.3%), 84/175 (48.0%) Ta and 68/175 (38.9%) T1. Average number of instillations = 13.25 ± 7.4. One hundred sixty-seven patients (95.4%) had complete induction. Forty-three patients (cumulative incidence 24.6%) were diagnosed with COVID-19. There is no difference between COVID-19 and NO-COVID group in age, gender or proportion of maintenance completed. COVID-19 group fatality rate = 1/43 (2.3%). Accumulated Chilean incidence 70–79 years = 6.3%. Chilean fatality rate 70–79 years = 14%. Conclusions According to our results, patients with NMIBC submitted to instillations with BCG have a lower case-fatality rate than the national registry of patients between 70 and 79 years (2.3% vs. 14%, respectively). Intravesical BCG could decrease the mortality due to COVID-19, so instillation schemes should not be suspended in a pandemic.


Author(s):  
Celestin Hategeka ◽  
Larry D Lynd ◽  
Cynthia Kenyon ◽  
Lisine Tuyisenge ◽  
Michael R Law

Abstract Implementing context-appropriate neonatal and paediatric advanced life support management interventions has increasingly been recommended as one of the approaches to reduce under-five mortality in resource-constrained settings like Rwanda. One such intervention is ETAT+, which stands for Emergency Triage, Assessment and Treatment plus Admission care for severely ill newborns and children. In 2013, ETAT+ was implemented in Rwandan district hospitals. We evaluated the impact of the ETAT+ intervention on newborn and child health outcomes. We used monthly time-series data from the DHIS2-enabled Rwanda Health Management Information System from 2012 to 2016 to examine neonatal and paediatric hospital mortality rates. Each hospital contributed data for 12 and 36 months before and after ETAT+ implementation, respectively. Using controlled interrupted time-series analysis and segmented regression model, we estimated longitudinal changes in neonatal and paediatric hospital mortality rates in intervention hospitals relative to matched concurrent control hospitals. We also studied changes in case fatality rate specifically for ETAT+-targeted conditions. Our study cohort consisted of 7 intervention hospitals and 14 matched control hospitals contributing 142 424 neonatal and paediatric hospital admissions. After controlling for secular trends and autocorrelations, we found that the ETAT+ implementation had no statistically significant impact on the rate of all-cause neonatal and paediatric hospital mortality in intervention hospitals relative to control hospitals. However, the case fatality rate for ETAT+-targeted neonatal conditions decreased immediately following implementation by 5% (95% confidence interval: −9.25, −0.77) and over time by 0.8% monthly (95% confidence interval: −1.36, −0.25) in intervention hospitals compared with control hospitals. Case fatality rate for ETAT+-targeted paediatric conditions did not decrease following the ETAT+ implementation. While ETAT+ focuses on improving the quality of hospital care for both newborns and children, we only found an impact on neonatal hospital mortality for ETAT+-targeted conditions that should be interpreted with caution given the relatively short pre-intervention period and potential regression to the mean.


Author(s):  
Paolo Pasquariello ◽  
Saverio Stranges

There is much discussion among clinicians, epidemiologists, and public health experts about why case fatality rate from COVID-19 in Italy (at 13.3% as of April 20, 2020, versus a global case fatality rate of 6.9%) is considerably higher than estimates from other countries (especially China, South Korea, and Germany). In this article, we propose several potential explanations for these differences. We suggest that Italy’s overall and relative case fatality rate, as reported by public health authorities, is likely to be inflated by such factors as heterogeneous reporting of coronavirus-related fatalities across countries and the iceberg effect of under-testing, yielding a distorted view of the global severity of the COVID-19 pandemic. We also acknowledge that deaths from COVID-19 in Italy are still likely to be higher than in other equally affected nations due to its unique demographic and socio-economic profile. Lastly, we discuss the important role of the stress imparted by the epidemic on the Italian healthcare system, which weakened its capacity to adequately respond to the sudden influx of COVID-19 patients in the most affected areas of the country, especially in the Lombardy region.


2020 ◽  
Author(s):  
Lei Cao ◽  
Ting-ting Huang ◽  
Jun-xia Zhang ◽  
Qi Qin ◽  
Si-yu Liu ◽  
...  

Abstract The worst-hit area of coronavirus disease 2019 (COVID-19) in China was Wuhan City and its affiliated Hubei Province, where the outbreak has been well controlled. The case fatality rate (CFR) is the most direct indicator to evaluate the hazards of an infectious disease. However, most reported CFR on COVID-19 represent a large deviation from reality. We aimed to establish a more accurate way to estimate the CFR of COVID-19 in Wuhan and Hubei and compare it to the reality. The daily case notification data of COVID-19 from December 8, 2019, to May 1, 2020, in Wuhan and Hubei were collected from the bulletin of the Chinese authorities. The instant CFR of COVID-19 was calculated from the numbers of deaths and the number of cured cases, the two numbers occurred on the same estimated diagnosis dates. The instant CFR of COVID-19 was 1.3%-9.4% in Wuhan and 1.2%-7.4% in Hubei from January 1 to May 1, 2020. It has stabilized at 7.69% in Wuhan and 6.62% in Hubei since early April. The cure rate was between 90.1% and 98.8% and finally stabilized at 92.3% in Wuhan and stabilized at 93.5% in Hubei. The mortality rates were 34.5/100 000 in Wuhan and 7.61/100 000 in Hubei. In conclusion, this approach reveals a way to accurately calculate the CFR, which may provide a basis for the prevention and control of infectious diseases.


2021 ◽  
Author(s):  
Tareef Fadhil Raham

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.


2020 ◽  
Author(s):  
Paolo Di Girolamo

Abstract The Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), which exploded in Wuhan (Hebei Region, China) in late 2019, has recently spread around the World, causing pandemic effects on humans. Italy, and especially its Northern regions around the Po Valley, has been facing severe effects in terms of infected individuals and casualties (more than 31.000 deaths and 255.000 infected people by mid-May 2020). While the spread and effective impact of the virus is primarily related to the life styles and social habits of the different human communities, environmental and meteorological factors also play a role. Among these, pollution from PM2.5/PM10 particles, which may directly impact on the human respiratory system or act as virus carrier, thus behaving as potential amplifying factors in the pandemic spread of SARS-CoV-2. Enhanced levels of PM2.5/PM10 particles in Northern Italy were observed over the two month period preceding the virus pandemic spread. Threshold levels for PM10 (<50 µg/m³) were exceeded on 20-35 days over the period January-February 2020 in many areas in the Po Valley, where major effects in terms of infections and casualties occurred, with levels in excess of 80 µg/m³ occasionally observed in the 1-3 weeks preceding the contagious activation around February 25th. Threshold values for PM2.5 indicted in WHO air quality guidelines (<25 µg/m³) were exceeded on more than 40 days over the period January-February 2020 in large portions of the Po Valley, with levels up to 70 µg/m³ observed in the weeks preceding the contagious activation. The evolution of particle matter concentration levels throughout the month of February 2020 was carefully monitored and results are reported in the paper.In this paper PM10 particle measurements are compared with epidemiologic parameters data. Specifically, a statistical analysis is carried out to correlate the infection rate, or incidence of the pathology, the mortality rate and the case fatality rate with PM concentration levels. The study considers epidemiologic data for all 110 Italian Provinces, as reported by the Italian Statistics Institute (ISTAT, 2020), over the period 20 February-31 March 2020. Corresponding PM10 concentration levels were collected from the network of air quality monitoring stations run by different Regional and Provincial Environment Agencies, covering the period 15-26 February 2020. The case fatality rate is found to be highly correlated to the average PM10 concentration, with a correlation coefficient of 0.89 and a slope of the regression line of (6.7±0.3)×10-3 m³/µg, which implies a doubling (from 3 to 6 %) of the mortality rate of infected patients for an average PM10 concentration increase from 22 to 27 μg/m³. Infection and mortality rates are also found to be correlated with PM10 concentration levels, with correlation coefficients being 0.82 and 0.80, respectively, and the slopes of the regression lines indicating a doubling (from 1 to 2 ‰) of the infection rate and a tripling (from 0.1 to 0.3 ‰) of the mortality rate for an average PM10 concentration increase from 25 to 29 μg/m³. Epidemiologic parameters data were also compared with population density data, but no clear evidence of a mutual correlation between these quantities was found. Considerations on the exhaled particles' sizes and concentrations, their residence times, transported viral dose and minimum infective dose, in combination with PM2.5/PM10 pollution measurements and an analytical microphysical model, allowed assessing the potential role of airborne transmission through virus-transmitting PM particles, in addition to droplet transmission, in conveying SARS-CoV-2 in the human respiratory system.


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