Seroprevalence and Risk Factors of SARS CoV-2 in Health Care Workers of Tertiary-Care Hospitals in the Province of Khyber Pakhtunkhwa, Pakistan

Haq, Mohsina; Rehman, Asif; Noor, Muhammad; Ahmed, Jawad; Aḥmad, Junaid; Irfan, Muhammad; Anwar, Saeed; Ahmad, Sajjad; Amin, Sakib Bin; Rahim, Fawad; Haq, Najib ul

doi:10.1101/2020.09.29.20203125

Cited by 2 publications

(4 citation statements)

References 22 publications

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“…Like, the study reported that the high prevalence rate of COVID-19 in health-care professionals is partly attributed to the lack of adequate supply of PPE to health-care workers. 18 The findings of our study are also fully aligned with the finding reported by Ranney et al 19 Whereas, COVID-19 is surrounded by many uncertainties in terms of its place of origin, etiology, clinical features, mortality rates, morbidity rates, risk prevention strategies, etc., this study is of paramount importance, as it will initiate a debate among the policy-makers and concerned stakeholders to take into account the protection of nurses and paramedics with the existing recommended preventive measures as well as the launch of additional interventions to make sure that a package comprising the adequate supply of PPE, tailored infection prevention and control training, and access to updated personal protection protocols by the WHO is made available to them.…”

Section: Discussionsupporting

confidence: 91%

“…This study is a part of a larger study (N = 1012) 18 by the investigators that aim at studying seroprevalence for COVID-19 among the various health-care providers working in a set of 3 selected public and private sector teaching hospitals of Peshawar, Pakistan. The larger study (not published yet) has found a comparatively very high prevalence among nurses and paramedics.…”

Section: Methodsmentioning

confidence: 99%

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Association of PPE Availability, Training, and Practices with COVID-19 Sero-Prevalence in Nurses and Paramedics in Tertiary Care Hospitals of Peshawar, Pakistan

Ahmad¹,

Anwar²,

Latif³

et al. 2020

Disaster med. public health prep.

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Background Nurses and paramedics by being the frontline workers of the healthcare profession need to be equipped with the relevant knowledge, skills and protective gears against different forms of infection, including COVID-19. Though the governments and concerned stakeholders have provided P.P.E.s, training and information to protect the healthcare professionals, however until now the scientific literature has virtually not reported the impact of P.P.Es availability, training and practices on the COVID-19 sero-prevalence among the nurses and paramedics. Objective This study aimed to assess the Impact of P.P.Es availability, training and practices on COVID-19 sero-prevalence among nurses and paramedics in teaching hospitals of Peshawar, Pakistan. Methods A cross-sectional survey was conducted with a total of 133 nurses and paramedics as subjects of the study. Results A univariate analysis was done for four variables. The findings indicate that the healthcare professionals (nurses & paramedics) who have received P.P.Es on time at the start of COVID-19 emergence has fewer chances of contracting the COVID-19 infection (O.R = 0.96); while the odds for P.P.Es supplies was 0.73, and the odds of hand hygiene training was 0.95. Conclusion The study concluded that the availability of the P.P.E.s, COVID-19 related training and compliance with W.H.O recommended practices against COVID-19 were instrumental in protection against the infection and its spread.

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Section: Discussionsupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Association of PPE Availability, Training, and Practices with COVID-19 Sero-Prevalence in Nurses and Paramedics in Tertiary Care Hospitals of Peshawar, Pakistan

Ahmad¹,

Anwar²,

Latif³

et al. 2020

Disaster med. public health prep.

Self Cite

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Section: Acknowledgmentsmentioning

confidence: 99%

“…Conducted at a hospital/healthcare clinic/ICU Younas, [142] Pakistan-Karachi, Sindh Conducted among blood donors Ali, [143] Pakistan-Khyber Pakhtunkhwa Focuses on patient cohort Haq, [144] Pakistan-Khyber Pakhtunkhwa Focuses on healthcare workers Javed, [145] Pakistan-multiple cities across Pakistan Focuses on working individuals Nisar, [146, p. 2] Pakistan-Peshawar Conducted among blood donors Jeewandara, [147] Sri Lanka-Colombo, Western Province Focuses on asymptomatic individuals . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.…”

Section: -36mentioning

confidence: 99%

SARS-CoV-2 infection fatality rates in India: systematic review, meta-analysis and model-based estimation

Zimmermann

Bhattacharya

Purkayastha

et al. 2021

Preprint

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Introduction Fervorous investigation and dialogue surrounding the true number of SARS-CoV-2 related deaths and implied infection fatality rates in India have been ongoing throughout the pandemic, and especially pronounced during the nations devastating second wave. We aim to synthesize the existing literature on the true SARS-CoV-2 excess deaths and infection fatality rates (IFR) in India, through a systematic search followed by viable meta-analysis. We then provide updated epidemiological model-based estimates of the wave 1, wave 2 and combined IFRs using an extension of the Susceptible-Exposed-Infected-Removed (SEIR) model, using data from April 1, 2020 to June 30, 2021. Methods Following PRISMA guidelines, the databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv, and SSRN for preprints (accessed through iSearch), were searched on July 3, 2021 (with results verified through August 15, 2021). Altogether using a two-step approach, 4,765 initial citations were screened resulting in 37 citations included in the narrative review and 19 studies with 41 datapoints included in the quantitative synthesis. Using a random effects model with DerSimonian-Laird estimation, we meta-analyze IFR1 which is defined as the ratio of the total number of observed reported deaths divided by the total number of estimated infections and IFR2 (which accounts for death underreporting in the numerator of IFR1). For the latter, we provide lower and upper bounds based on the available range of estimates of death undercounting, often arising from an excess death calculation. The primary focus is to estimate pooled nationwide estimates of IFRs with the secondary goal of estimating pooled regional and state-specific estimates for SARS-CoV-2 related IFRs in India. We also try to stratify our empirical results across the first and the second wave. In tandem, we present updated SEIR model estimates of IFRs for waves 1, 2, and combined across the waves with observed case and death count data from April 1, 2020 to June 30, 2021. Results For India countrywide, underreporting factors (URF) for cases (sourced from serosurveys) range from 14.3-29.1 in the four nationwide serosurveys; URFs for deaths (sourced from excess deaths reports) range from 4.4-11.9 with cumulative excess deaths ranging from 1.79-4.9 million (as of June 2021). Nationwide pooled IFR1 and IFR2 estimates for India are 0.097% (95% confidence interval [CI]: 0.067 - 0.140) and 0.365% (95% CI: 0.264 - 0.504) to 0.485% (95% CI: 0.344 - 0.685), respectively, again noting that IFR2 changes as excess deaths estimates vary. Among the included studies in this meta-analysis, the IFR1 generally appear to decrease over time from the earliest study end date to the latest study end date (from 4 June 2020 to 6 July 2021, IFR1 changed from 0.199 to 0.055%), whereas a similar trend is not as readily evident for IFR2 due to the wide variation in excess death estimates (from 4 June 2020 to 6 July 2021, IFR2 ranged from (0.290-1.316) to (0.241-0.651) %). Nationwide SEIR model-based combined estimates for IFR1 and IFR2 are 0.101% (95% CI: 0.097 - 0.116) and 0.367% (95% CI: 0.358 - 0.383), respectively, which largely reconcile with the empirical findings and concur with the lower end of the excess death estimates. An advantage of such epidemiological models is the ability to produce daily estimates with updated data with the disadvantages being that these estimates are subject to numerous assumptions, arduousness of validation and not directly using the available excess death data. Whether one uses empirical data or model-based estimation, it is evident that IFR2 is at least 3.6 times more than IFR1. Conclusion When incorporating case and death underreporting, the meta-analyzed cumulative infection fatality rate in India varies from 0.36%-0.48%, with a case underreporting factor ranging from 25-30 and a death underreporting factor ranging from 4-12. This implies, by June 30, 2021, India may have seen nearly 900 million infections and 1.7-4.9 million deaths when the reported numbers stood at 30.4 million cases and 412 thousand deaths (covid19india.org) with an observed case fatality rate (CFR) of 1.35%. We reiterate the need for timely and disaggregated infection and fatality data to examine the burden of the virus by age and other demographics. Large degrees of nationwide and state-specific death undercounting reinforce the call to improve death reporting within India.

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Real-world experience of SARS-CoV-2 antibody assays in UK healthcare workers

et al. 2021

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Seroprevalence and Risk Factors of SARS CoV-2 in Health Care Workers of Tertiary-Care Hospitals in the Province of Khyber Pakhtunkhwa, Pakistan

Cited by 2 publications

References 22 publications

Association of PPE Availability, Training, and Practices with COVID-19 Sero-Prevalence in Nurses and Paramedics in Tertiary Care Hospitals of Peshawar, Pakistan

Association of PPE Availability, Training, and Practices with COVID-19 Sero-Prevalence in Nurses and Paramedics in Tertiary Care Hospitals of Peshawar, Pakistan

SARS-CoV-2 infection fatality rates in India: systematic review, meta-analysis and model-based estimation

Real-world experience of SARS-CoV-2 antibody assays in UK healthcare workers

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