Hospitalization, death, and probable reinfection in Peruvian healthcare workers infected with SARS-CoV-2: a national retrospective cohort study

BACKGROUND

Peru has some of the worst outcomes worldwide as a result of the SARS-CoV-2 pandemic; it is presumed that this has also affected healthcare workers. This study aimed to establish whether occupation and other non-occupational variables were risk factors for possible reinfection, hospitalization, and mortality from COVID-19 in cohorts of Peruvian healthcare workers infected with SARS-CoV-2.

METHODS

Retrospective cohort study. Healthcare workers who presented SARS-CoV-2 infection between March 1, 2020, and August 6, 2021, were included. Occupational cohorts were reconstructed from the following sources of information: National Epidemiological Surveillance System, molecular tests (NETLAB), results of serology and antigen tests (SICOVID-19), National Registry of Health Personnel (INFORHUS), and National Information System of Deaths (SINADEF). The incidence of probable reinfection, hospitalization, and death from COVID-19 was obtained in the cohorts of technicians and health assistants, nursing staff, midwives, dentists, doctors, and other healthcare workers. We evaluated whether the occupation and other non-occupational variables were risk factors for probable reinfection, hospitalization, and death from COVID-19 using log-binomial and probit binomial models, obtaining the adjusted relative risk (RR_AJ).

RESULTS

90,398 healthcare workers were included in the study. Most cases were seen in technicians and health assistants (38.6%), and nursing staff (25.6%). 8.1% required hospitalization, 1.7% died from COVID-19, and 1.8% had probable reinfection. A similar incidence of probable reinfection was found in the six cohorts (1.7-1.9%). Doctors had a higher incidence of hospitalization (13.2%) and death (2.6%); however, they were also those who presented greater susceptibility linked to non-occupational variables (age and comorbidities). The multivariate analysis found that doctors (RR_AJ = 1.720; CI 95: 1.569-1.886) had a higher risk of hospitalization and that the occupation of technician and health assistant was the only one that constituted a risk factor for mortality from COVID-19 (RR_AJ = 1.256; 95% CI: 1.043-1.512).

CONCLUSIONS

Peruvian technicians and health assistants would have a higher risk of death from COVID-19 than other healthcare workers, while doctors have a higher incidence of death probably linked to the high frequency of non-occupational risk factors. Doctors present a higher risk of hospitalization independent of comorbidities and age; likewise, all occupations show a similar risk of probable reinfection.

Epidemiological Characteristics of Deaths from COVID-19 in Peru during the Initial Pandemic Response

BACKGROUND AND AIM

Peru is the country with the highest mortality rate from COVID-19 globally, so the analysis of the characteristics of deaths is of national and international interest. The aim was to determine the epidemiological characteristics of deaths from COVID-19 in Peru from 28 March to 21 May 2020.

METHODS

Deaths from various sources were investigated, including the COVID-19 Epidemiological Surveillance and the National System of Deaths (SINADEF). In all, 3851 deaths that met the definition of a confirmed case and had a positive result of RT-PCR or rapid test IgM/IgG, were considered for the analysis. We obtained the epidemiological variables and carried out an analysis of time defined as the pre-hospital time from the onset of symptoms to hospitalization, and hospital time from the date of hospitalization to death.

RESULTS

Deaths were more frequent in males (72.0%), seniors (68.8%) and residents of the region of Lima (42.7%). In 17.8% of cases, the death occurred out-of-hospital, and 31.4% had some comorbidity. The median of pre-hospital time was 7 days (IQR: 4.0-9.0) and for the hospital time was 5 days (IQR: 3.0-9.0). The multivariable analysis with Poisson regression with robust variance found that the age group, comorbidity diagnosis and the region of origin significantly influenced pre-hospital time; while sex, comorbidity diagnosis, healthcare provider and the region of origin significantly influenced hospital time.

CONCLUSION

Deaths occurred mainly in males, seniors and on the coast, with considerable out-of-hospital deaths. Pre-hospital time was affected by age group, the diagnosis of comorbidities and the region of origin; while, hospital time was influenced by gender, the diagnosis of comorbidities, healthcare provider and the region of origin.