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Restricted Prevalence Rates of COVID-19's Infectivity, Hospitalization, Recovery, Mortality in the USA and Their Implications.

ABSTRACT: This article constructs and demonstrates an alternate probabilistic approach (using incidence rate restricted model), compared with the deterministic mathematical models such as SIR, to capture the impact of healthcare efforts on the prevalence rate of the COVID-19's infectivity, hospitalization, recovery, and mortality in the eastern, central, mountain, and pacific time zone states in the USA. We add additional new properties for the incidence rate restricted Poisson probability distribution. With new properties, our method becomes feasible to comprehend not only the patterns of the prevalence rate of the COVID-19's infectivity, hospitalization, recovery, and mortality but also to quantitatively assess the effectiveness of social distancing, healthcare management's efforts to hospitalize the patients, the patient's immunity to recover, and lastly the unfortunate mortality itself. To make regional comparisons (as the people's movement is far more frequent within than outside the regional zone on daily basis), we group the COVID-19 data in terms of eastern, central, mountain, and pacific zone states. Several non-intuitive findings in the data results are noticed. They include the existence of imbalance, different vulnerability, and risk reduction in these four regions. For example, the impact of healthcare efforts is high in the recovery category in the pacific states. The impact is less in the hospitalization category in the mountain states. The least impact is seen in the infectivity category in the eastern zone states. A few thoughts on future research work are cited. It requires collecting rich data on COVID-19 and extracting valuable information for better public health policies.

SUBMITTER: Shanmugam R

PROVIDER: S-EPMC7546524 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Restricted Prevalence Rates of COVID-19's Infectivity, Hospitalization, Recovery, Mortality in the USA and Their Implications.

Shanmugam Ramalingam R

Journal of healthcare informatics research 20201009 2

This article constructs and demonstrates an alternate probabilistic approach (using incidence rate restricted model), compared with the deterministic mathematical models such as SIR, to capture the impact of healthcare efforts on the prevalence rate of the COVID-19's infectivity, hospitalization, recovery, and mortality in the eastern, central, mountain, and pacific time zone states in the USA. We add additional new properties for the incidence <i>rate restricted Poisson</i> probability distribu ...[more]

PMID: 33073166

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Project description:ImportanceAfter abrupt closures of businesses and public gatherings in the US in late spring 2020 due to the COVID-19 pandemic, by mid-May 2020, most states reopened their economies. Owing in part to a lack of earlier data, there was little evidence on whether state reopening policies influenced important pandemic outcomes-COVID-19-related hospitalizations and mortality-to guide future decision-making in the remainder of this and future pandemics.ObjectiveTo investigate changes in COVID-19-related hospitalizations and mortality trends after reopening of US state economies.Design setting and participantsUsing an interrupted time series approach, this cross-sectional study examined trends in per-capita COVID-19-related hospitalizations and deaths before and after state reopenings between April 16 and July 31, 2020. Daily state-level data from the University of Minnesota COVID-19 Hospitalization Tracking Project on COVID-19-related hospitalizations and deaths across 47 states were used in the analysis.ExposuresDates that states reopened their economies.Main outcomes and measuresState-day observations of COVID-19-related hospitalizations and COVID-19-related new deaths per 100 000 people.ResultsThe study included 3686 state-day observations of hospitalizations and 3945 state-day observations of deaths. On the day of reopening, the mean number of hospitalizations per 100 000 people was 17.69 (95% CI, 12.54-22.84) and the mean number of daily new deaths per 100 000 people was 0.395 (95% CI, 0.255-0.536). Both outcomes displayed flat trends before reopening, but they started trending upward thereafter. Relative to the hospitalizations trend in the period before state reopenings, the postperiod trend was higher by 1.607 per 100 000 people (95% CI, 0.203-3.011; P = .03). This estimate implied that nationwide reopenings were associated with 5319 additional people hospitalized for COVID-19 each day. The trend in new deaths after reopening was also positive (0.0376 per 100 000 people; 95% CI, 0.0038-0.0715; P = .03), but the change in mortality trend was not significant (0.0443; 95% CI, -0.0048 to 0.0933; P = .08).Conclusions and relevanceIn this cross-sectional study conducted over a 3.5-month period across 47 US states, data on the association of hospitalizations and mortality with state reopening policies may provide input to state projections of the pandemic as policy makers continue to balance public health protections with sustaining economic activity.

Project description:The analysis of systematically collected data for coronavirus disease 2019 (COVID-19) infectivity and death rates has revealed, in many countries around the world, a typical oscillatory pattern with a 7-day (circaseptan) period. Additionally, in some countries, 3.5-day (hemicircaseptan) and 14-day periodicities have also been observed. Interestingly, the 7-day infectivity and death rate oscillations are almost in phase, showing local maxima on Thursdays/Fridays and local minima on Sundays/Mondays. These observations are in stark contrast to a known pattern correlating the death rate with the reduced medical staff in hospitals on the weekends. While we cannot exclude the possibility that a significant portion of the observed oscillations is associated with the reporting of the individual cases, other reasons might contribute at least partly to these data. One possible hypothesis addressing these observations is that they reflect gradually increasing stress with the progressing week, which can trigger the higher death rates on Thursdays/Fridays. Moreover, assuming the weekends provide the likely time for new infections, the maximum number of new cases might fall, again, on Thursdays/Fridays. These observations deserve further study to provide a better understanding of COVID-19 dynamics.IMPORTANCE The infectivity and death rates for COVID-19 have been observed in many countries around the world as well as in the collective data of the whole world. These oscillations show distinct circaseptan periodicity, which could be associated with numerous biological reasons as well as with improper reporting of the data collected. Since very different results are observed in different countries and even continents, such as Sweden (very significant oscillations) or India (almost no oscillations), these data provide a very important message about different conditions under which the disease is spread or is reported, which, in turn, could serve as guidance tools in future epidemics. It is necessary that follow-up studies track the observed differences and fully reliably address their origins.

Project description:ImportanceAnemia is common and has been associated with poor outcomes in the critically ill population, yet the timing and extent of hemoglobin recovery remains incompletely described, which may have important implications for clinical outcomes following discharge from intensive care.ObjectivesTo describe longitudinal changes in anemia status during and after critical illness and assess the associations between hemoglobin concentrations and postdischarge mortality.Design, setting, and participantsA population-based cohort study was conducted from January 1, 2010, to December 31, 2016, in Olmsted County, Minnesota; data analysis was performed from June 1 to December 30, 2019. Participants included 6901 adults (age ≥18 years) admitted to intensive care.Main outcomes and measuresHemoglobin concentrations in the 12 months before hospitalization, during hospitalization, and in the 12 months after discharge, categorized by anemia severity (mild, hemoglobin ≥10.0 to <12.0 g/dL in women or ≥10.0 to <13.5 g/dL in men; moderate, hemoglobin ≥8.0 to <10.0 g/dL; and severe, hemoglobin <8.0 g/dL). Complete recovery from anemia, defined as attainment of nonanemic status by 12 months post hospitalization, and 12-month mortality were also evaluated.ResultsOf the 6901 patients included in the study, 3792 were men (55%); median (interquartile range [IQR]) age was 67 (IQR, 52-79) years. Prehospitalization hemoglobin concentrations were available in 83% of the population (n = 5694), with median hemoglobin concentrations of 13.1 (IQR, 11.6-14.4) g/dL. Forty-one percent of the patients (n = 2320) had anemia preceding hospitalization. Hemoglobin values at hospital discharge were 10.8 g/dL (IQR, 9.5-12.4 g/dL), with 80% (n = 5182 of 6460) having anemia: 58% mild, 39% moderate, and 3% severe. The prevalence of anemia post hospitalization was 56% (95% CI, 55%-58%) at 3 months, 52% (95% CI, 50%-54%) at 6 months, and 45% (95% CI, 43%-47%) at 12 months among those alive with available hemoglobin measurements. Rates of complete recovery from anemia at 12 months were 58% (95% CI, 56%-61%) for mild anemia, 39% (95% CI, 36%-42%) for moderate anemia, and 24% (95% CI, 15%-34%) for severe anemia. Of those without baseline anemia surviving hospitalization, 74% of the patients were anemic at hospital discharge, with rates of complete 12-month recovery of 73% (95% CI, 69%-76%) for mild anemia, 62% (95% CI, 57%-68%) for moderate anemia, and 59% (95% CI, 35%-82%) for severe anemia. Higher hospital discharge hemoglobin concentrations were associated with decreased mortality after multivariable adjustment (hazard ratio, 0.95 per 1-g/dL increase; 95% CI, 0.90-0.99, P = .02).Conclusions and relevanceThe findings of this study suggest that anemia is common and often persistent in the first year after critical illness. Further studies are warranted to identify distinct anemia recovery profiles and assess associations with clinical outcomes.

Dataset Information

Restricted Prevalence Rates of COVID-19's Infectivity, Hospitalization, Recovery, Mortality in the USA and Their Implications.

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Restricted Prevalence Rates of COVID-19's Infectivity, Hospitalization, Recovery, Mortality in the USA and Their Implications.

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