SARS-CoV-2 infection in health care workers during the first 2-years of the pandemic at a cancer hospital in Mexico

Ibanes-Gutierrez, Cyntia; Martínez-Rivera, Nancy; Martin-Onraet, Alexandra; Rivera-Buendia, Frida; Piñeirua-Menendez, Alicia; Villaseñor-Echavarri, Rodrigo; Serrano-Ortega, Janis; Vilar-Compte, Diana

doi:10.1016/j.ajic.2023.12.004

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…Both types of study have shown that natural and artificial immunity both wane over time and have led to the adaptation of recommendations regarding vaccination schedules [ 8 , 17 , 19 , 27 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Common epidemiological indicators of frequency in other studies showed increases in the number of reinfections and primo-infections in the Omicron era, similar to our study [ 25 , 26 , 43 , 44 ]. The previously published study on the first SARS-CoV-2 infection, on the same population of HCWs, showed a higher severity of the cases registered in HCWs from the high-risk departments [ 18 ].…”

Section: Discussionsupporting

confidence: 91%

“…The higher frequency of infections and reinfections during Omicron circulation reported in other studies has been explained by changes in the transmissibility of Omicron variants and vaccine effectiveness [ 16 , 43 , 44 , 48 ]. Although during the study period the HCWs wore PPE in healthcare activities, in the community they were exposed to asymptomatic or suspected COVID-19 cases, as restrictions were fewer during Omicron compared to other waves.…”

Section: Discussionmentioning

confidence: 89%

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Hybrid Immunity and the Incidence of SARS-CoV-2 Reinfections during the Omicron Era in Frontline Healthcare Workers

Chivu,

Crăciun,

Pițigoi

et al. 2024

Vaccines

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During the coronavirus disease (COVID-19) pandemic healthcare workers (HCWs) acquired immunity by vaccination or exposure to multiple variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our study is a comparative analysis between subgroups of HCWs constructed based on the number of SARS-CoV-2 infections, vaccination, and the dominant variant of SARS-CoV-2 in the population. We collected and analyzed data using the χ2 test and density incidence of reinfections in Microsoft Excel for Mac, Version 16.84, and MedCalc®, 22.026. Of the 829 HCWs, 70.1% (581) had only one SARS-CoV-2 infection and 29.9% (248) had two infections. Of the subjects with two infections, 77.4% (192) worked in high-risk departments and 93.2% (231) of the second infections were registered during Omicron dominance. The density incidence of reinfections was higher in HCWs vaccinated with the primary schedule than those vaccinated with the first booster, and the incidence ratio was 2.8 (95% CI: 1.2; 6.7). The probability of reinfection was five times lower (95% CI: 2.9; 9.2) in HCWs vaccinated with the primary schedule if the first infection was acquired during Omicron dominance. The subjects vaccinated with the first booster had a density incidence of reinfection three times lower (95% CI: 1.9; 5.8) if the first infection was during Omicron. The incidence ratio in subgroups constructed based on characteristics such as gender, age group, job category, and department also registered significant differences in density incidence. The history of SARS-CoV-2 infection by variant is important when interpreting and understanding public health data and the results of studies related to vaccine efficacy for hybrid immunity subgroup populations.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 89%

Hybrid Immunity and the Incidence of SARS-CoV-2 Reinfections during the Omicron Era in Frontline Healthcare Workers

Chivu,

Crăciun,

Pițigoi

et al. 2024

Vaccines

View full text Add to dashboard Cite

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“…Follow-up was conducted between July and August 2021 ( N = 2,300), when the Delta variant was dominant, and the last contact occurred in March 2022 ( N = 1,400), during the last phase of the Omicron-1 variant. During these two waves no lockdown was enforced ( 27 ). Surveys were collected using a one-stage and probabilistic sample, stratified for each state of the country ( n = 32).…”

Section: Methodsmentioning

confidence: 99%

Predictors of persistent moderate and severe food insecurity in a longitudinal survey in Mexico during the COVID-19 pandemic

Gaitán-Rossi,

Hernández-Solano,

López-Caballero

et al. 2024

Front. Public Health

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BackgroundHousehold food insecurity (HFI) increased in Latin America by 9% between 2019 and 2020. Scant evidence shows who was unable to recover from the COVID-19 pandemic. Our aim was to use a Machine Learning (ML) approach to identify consistent and influential predictors of persistent moderate or severe HFI over 2 years.MethodsWe use a three-wave longitudinal telephone survey with a probabilistic sample representative of the Mexican population. With a response rate of 51.3 and 60.8% for the second and third waves, the final sample size consisted of 1,074 individuals. The primary outcome was persistent HFI, i.e., respondents who reported moderate or severe HFI in 2021 and 2022. Twelve income-related predictors were measured in 2020, including baseline HFI. We employed 6 supervised ML algorithms to cross-validate findings in models, examined its precision with 4 standard performance indicators to assess precision, and used SHAP values (Shapley Additive exPlanations) to identify influential predictors in each model.ResultsPrevalence of persistent moderate/severe HFI in 2021 and 2022 was 8.8%. Models with only a HFI 2020 baseline measure were used as a reference for comparisons; they had an accuracy of 0.79, a Cohen’s Kappa of 0.57, a sensitivity of 0.68, and a specificity of 0.88. When HFI was substituted by the suite of socioeconomic indicators, accuracy ranged from 0.70 to 0.84, Cohen’s Kappa from 0.40 to 0.67, sensitivity from 0.86 to 0.90, and specificity from 0.75 to 0.82. The best performing models included baseline HFI and socioeconomic indicators; they had an accuracy between 0.81 and 0.92, a Cohen’s Kappa between 0.61 and 0.85, a sensitivity from 0.74 to 0.95, and a specificity from 0.85 to 0.92. Influential and consistent predictors across the algorithms were baseline HFI, socioeconomic status (SES), adoption of financial coping strategies, and receiving government support.DiscussionPersistent HFI can be a relevant indicator to identify households that are less responsive to food security policies. These households should be prioritized for innovative government support and monitored to assess changes. Forecasting systems of HFI can be improved with longitudinal designs including baseline measures of HFI and socioeconomic predictors.

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SARS-CoV-2 infection in health care workers during the first 2-years of the pandemic at a cancer hospital in Mexico

Cited by 2 publications

References 15 publications

Hybrid Immunity and the Incidence of SARS-CoV-2 Reinfections during the Omicron Era in Frontline Healthcare Workers

Hybrid Immunity and the Incidence of SARS-CoV-2 Reinfections during the Omicron Era in Frontline Healthcare Workers

Predictors of persistent moderate and severe food insecurity in a longitudinal survey in Mexico during the COVID-19 pandemic

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