Epidemiological philosophy of pandemics
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Abstract
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.
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SciScore for 10.1101/2021.02.24.21252304: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This limitation leads to an underestimation of asymptomatic infections which were estimated to be 10–70% of total true infections elsewhere .21 Furthermore, limited access to testing could result in undercounting of deaths. Another limitation in this study (due to estimation coverage in part) is that we estimate confirmed cases / M and …
SciScore for 10.1101/2021.02.24.21252304: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This limitation leads to an underestimation of asymptomatic infections which were estimated to be 10–70% of total true infections elsewhere .21 Furthermore, limited access to testing could result in undercounting of deaths. Another limitation in this study (due to estimation coverage in part) is that we estimate confirmed cases / M and CFR. IMR estimates are more convenient to derive MR vs IMR equation instead of CFR which represent only part of the problem. One of further limitations is the relatively small number of the study sample. In real-time, estimates of the case fatality ratio (CFR) and infection fatality ratio (IFR) can be biased upwards by under-reporting of cases and downwards by failure to account for the delay from confirmation-to-death. Virulence of pathogens depends largely on the previous immunity of the host whether cross-reacting or due to previous infection or vaccination. Clinical trials should proceed to identify the role of both highly transmitted and not highly transmitted viruses and pathogens. These studies should also answer the question: whether a high load of a low virulent viral infection among not previously exposed subjects leads to high mortality. Factors such as mobility, social distancing policies, population density, and host factors can interfere greatly with the no. of cases. The scope of this study was not designed to look for causes of variances in no. of cases with different times and places. Anyhow, we test how the total number of cas...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a protocol registration statement.
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