key: cord-0940695-oqrsk5ds
authors: Timelli, Laura; Liuzzi, Giuseppina; Cannavacciuolo, Alessandro; Petrosillo, Nicola; Puro, Vincenzo; Girardi, Enrico
title: Association of COVID-19 case-fatality rate with disease burden: an ecological analysis in Italy during the first wave.
date: 2021-08-19
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2021.08.032
sha: 8c4b76e3f1f230092bead556828db72ba14e88e0
doc_id: 940695
cord_uid: oqrsk5ds

OBJECTIVES: : Case-fatality-rate (CFR) of COVID-19 during the first wave of pandemic showed significant geographic heterogeneity in Italy. By using an ecological approach, we aimed to explore possible association between CFR and measures of disease burden in Italian regions. METHODS: : We analyzed cumulated regional data for period February 24–May 11, 2020, to assess the association of CFR with cumulative incidence of COVID-19 and ratio between maximum number of COVID-19 patients in intensive care units (ICU) and ICU beds available before the pandemic (ICU load) adjusting for median age of patients at disease, number of nasopharyngeal swabs performed per confirmed case and prevalence chronic diseases. RESULTS: : During the study period, COVID-19 CFR in Italian regions ranged between 5.0% and 18.4%. In multivariable regression, CFR was significantly associated with cumulative incidence (relative rate [RR]=1.02 per 100 cases/1 million increase), median age (RR=1.07 per 1 year increase) and ICU load (RR=1.72, 2.18 and 2.57, for >40%-70% vs <=40%, 70%-140% and >=140 vs <=40%, respectively). CONCLUSIONS: : High burden of COVID-19 may contribute to increase fatality of the disease, possibly by increasing demand for care of critically ill patients beyond health system capability.

Estimates of the case-fatality-rate (CFR) of COVID-19 varied greatly among countries during the first phase of the pandemic [World Health Organization 2020 ]. An analysis of data from nine countries found that two-third of this heterogeneity is accounted for by differences of age distribution of cases [Sudharsanan et al., 2020] . Other factors, such as prevalence of comorbidities and rate of detection of SARS-COV-2, contribute to variability of CFR [Emanuel et al., 2020] . In addition, Ergonül [Ergönül et al., 2020] reported that a larger availability of hospital beds at country level is associated with lower CFR. Indeed, it has been suggested that the overburden on health care system caused by sudden increase of number of cases may contribute to increase CFR by reducing standard of care of affected individuals in need of hospital care [Emanuel et al., 2020] .Data on this aspect however, are limited.

In Italy incidence and CFR of COVID-19 during the first wave of pandemic showed significant geographic heterogeneity [ISTAT, 2020] . By using an ecological approach, we aimed to explore possible association between CFR and measures of disease burden.

Italy is administratively divided in 19 regions and 2 autonomous provinces (PA). Since the 24th of February 2020, the Italian Ministry of Health, started the daily collection of new Covid-19 cases, where each Region and PA provided the number of deaths, number of hospitalized cases, and number of cases in intensive care unit (ICU). According the regional burden of COVID-19 patients, a proportion of ICU were dedicated to COVID patients or, were possible, separated areas for COVID-19 patients were created in ICU where also non COVID-19 patients were admitted [Pasin et al., 2020] . In highest burden regions during the peak of the first wave of the epidemic, virtually all ICU beds were dedicated to COVID-19 patients and non COVID-19 have been transferred outside the region [Grasselli et al., 2020] . We analyzed cumulated publicly available Italian regional data for the period February 24- May 11, 2020 [Github, 2020 . CFR was calculated as proportion of individuals died with confirmed Covid-19 on total reported cases. We used correlation coefficient, univariate and multivariable (backward selection, p=0.20) negative binomial regression to assess the association of CFR with the following variables: cumulative incidence of COVID, as a measure of overall disease burden; ratio between maximum number of COVID-19 patients in ICU and ICU beds available before the pandemic (ICU load), as a proxy of capacity to care for severely ill patients; median age at disease [ISS, 2020] ; prevalence of chronic disease including diabetes, cardiovascular diseases and chronic obstructive pulmonary disease [Osservatorio sulla salute, 2019]; number of SARS Cov2 nasopharyngeal swabs performed per COVID-19 case diagnosed, as a proxy of probability of detecting asymptomatic/mildly symptomatic cases.

All the variables were considered as continuum measures except ICU load categorized into three classes, according to the distribution in quartiles: <=40%, >40%-70%, 70%-140% and ≥140%.

During the period considered 219,214 cases were reported with a cumulative incidence of 364/100,000 inhabitants. At regional level, incidence ranged between 58 and 912/100,000. Table 1 reports the maximum number of COVID-19 patients in ICU, the number of ICU beds and ICU load by region; we note that ICU load varied between a minimum of around 16% and a maximum of 253%. 

This analysis shows that in Italy, during first phase of the pandemic, CFR of COVID-19 at regional level was significantly associated, as well as with age at disease, with overall burden and ICU demand due to COVID-19.

While most of previous studies on variation in CFR of COVID-19 involved cross-countries comparisons, this analysis was conducted in a single country in which health care standards are defined at national level, thus it is unlikely that regional differences in the overall quality of care may explain the observed differences in CFR. However, in most severely hit Our observation is also consistent with the results of a study conducted in the US in which a higher ICU patient load has been found to be associated with increased COVID-19 inhospital mortality [Bravata et al., 2020] .

In a previous study in China, it was observed that Hubei province, which had the highest COVID-19 incidence during first wave of the epidemic, had also highest CFR compared to other provinces, and authors postulated that this could be attributed to differences in case ascertainment [Leung et al., 2020] . In the adjusted estimates, we found no association between CFR and testing rates, suggesting that it is unlikely that differences in the availability of and approaches to SARS-CoV-2 testing may account for regional variability of CFR. Indeed, testing policy in Italy followed national guidelines, although it is possible however, that in areas with highest incidence even severely ill patients were not tested for SARS-Cov2, as suggested by significant numbers of excess deaths recorded in these areas [Piccininni et al., 2020] .

A major limitation of this analysis is that CFR overestimates true infection fatality rate.

Moreover, we used an ecologic approach, which is subject to bias due to lack of individual data [Wakefield et al., 2008] .It should be noted that our data were aggregated at a regional level and therefore it was not possible to standardize them by age and sex.

Nonetheless, our results are consistent with an analysis of Italian national surveillance data [ISS, 2021] , which also shows a positive correlation between standardized CFR and standardized incidence. In that analysis, however, the COVID-19 burden on ICUs was not . In our analysis we used regional prevalence of population with at least one chronic disease and this data does not seem to have any effect on CFR. Possible explanations, could be that we used data from all the population, not adjusted for age, data from a sample survey and not specific to particular comorbities.

In conclusion, this analysis suggests that rapid increase in incidence of COVID-19 may contribute to increase fatality of this disease. These findings underscore the need of timely adoption of mitigation measures also during subsequent epidemic waves to ensure appropriate care to all affected patients and limitation of mortality.

Funding Source: None Ethical Approval: This study is performed with data from routine surveillance activity and does not require ethical clearance.

Surviving Sepsis Campaign: Guidelines on the Management of Critically Ill Adults with Coronavirus Disease 2019 (COVID-19)

Association of Intensive Care Unit Patient Load and Demand With Mortality Rates in US

Fair Allocation of Scarce Medical Resources in the Time of Covid-19

National case fatality rates of the COVID-19 pandemic

GITHUB

Critical Care Utilization for the COVID-19 Outbreak in Lombardy, Italy: Early Experience and Forecast During an Emergency Response

First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment

Regional COVID-19 Network for Coordination of SARS-CoV-2 outbreak in Veneto

Use of all cause mortality to quantify the consequences of covid-19 in Nembro, Lombardy: descriptive study

Intensive Care Unit Strain and Mortality Risk Among Critically Ill Patients With COVID-19-There Is No "Me" in COVID

The Contribution of the Age Distribution of Cases to COVID-19 Case Fatality Across Countries : A Nine-Country Demographic Study

Predictors of mortality in hospitalized COVID-19 patients: A systematic review and meta-analysis

Ecologic studies revisited. Annual review of public health

Estimating mortality from COVID-19. Scientific Brief