Prevalence of COVID-19 in Iran: results of the first survey of the Iranian COVID-19 Serological Surveillance programme

Khalagi, Kazem; Gharibzadeh, Safoora; Khalili, Davood; Mansournia, Mohammad Ali; Samiee, Siamak Mirab; Aghamohamadi, Saeide; Roodaki, Maryam Mir-Mohammad-Ali; Hashemi, Seyed Mahmoud; Tayeri, Katayoun; Tabar, Hengameh Namdari; Azadmanesh, Kayhan; Tabrizi, Jafar Sadegh; Mohammad, Kazem; Hajipour, Firoozeh; Namaki, Saeed; Raeisi, Alireza; Ostovar, Afshin

doi:10.1016/j.cmi.2021.06.002

Cited by 41 publications

(31 citation statements)

References 12 publications

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“…Additionally, the overall prevalence estimates were adjusted not only for sex and age groups, but also for test performance to make the findings representative of the study population. The non-response rate at the household level was relatively low compared to other population-based survey [ 15 , 17 , 30 – 36 ]. Finally, Individuals with current SARS-CoV-2 symptoms were excluded to avoid an inflated proportion of individuals with negative tests which could underestimate the seroprevalence.…”

Section: Discussionmentioning

confidence: 70%

SARS-CoV-2 antibody seroprevalence in Lebanon: findings from the first nationwide serosurvey

Hoballah¹,

Haidari²,

Siblany

et al. 2022

BMC Infect Dis

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Background Lebanon, a small country in the Middle East, remains severely affected by the COVID-19 pandemic. Seroprevalence surveys of anti-SARS-CoV-2 antibodies provide accurate estimates of SARS-CoV-2 infection and hence evaluate the extent of the pandemic. The present study aimed to evaluate the prevalence of SARS-CoV-2 antibodies in Lebanon and to compare the estimated cumulative number of COVID-19 cases with the officially registered number of laboratory-confirmed cases up to January 15, 2021. Methods A nationwide population-based serosurvey study was conducted in Lebanon between December 7, 2020, and January 15, 2021, before the initiation of the national vaccination program. The nCOVID-19 IgG & IgM point-of-care (POCT) rapid test was used to detect the presence of anti-SARS-COV-2 immunoglobulin G (IgG) in the blood. Seroprevalence was estimated after weighting for sex, age, and area of residence and adjusting for the test performance. Results Of the 2058 participants, 329 were positive for IgG SARS-COV-2, resulting in a crude seroprevalence of 16.0% (95% CI 14.4–17.6). The weighed seroprevalence was 15.9% (95% CI of 14.4 and 17.4). After adjusting for test performance, the population weight-adjusted seroprevalence was 18.5% (95% CI 16.8–20.2). This estimate implies that 895,770 individuals of the general population were previously infected by COVID-19 up to January 15, 2021 in Lebanon. The overall estimated number of subjects with previous SARS-CoV-2 infection was three times higher than the officially reported cumulative number of confirmed cases. Seroprevalence was similar across age groups and sexes (p-value > 0.05). However, significant differences were revealed across governorates. Conclusions Our results suggest that the Lebanese population is still susceptible to SARS-CoV-2 infection and far from achieving herd immunity. These findings represent an important contribution to the surveillance of the COVID-19 pandemic in Lebanon and to the understanding of how this virus spreads. Continued surveillance for COVID-19 cases and maintaining effective preventive measures are recommended to control the epidemic spread in conjunction with a national vaccination campaign to achieve the desired level of herd immunity against COVID-19.

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Section: Discussionmentioning

confidence: 70%

SARS-CoV-2 antibody seroprevalence in Lebanon: findings from the first nationwide serosurvey

Hoballah¹,

Haidari²,

Siblany

et al. 2022

BMC Infect Dis

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“…To the best of our knowledge, no similar serosurveys have been done in the same period as our study in Iran (after the third wave) either at the national or regional level, and all available studies pertains to previous waves [ 9 , 28 – 31 ]; hence, we are not able to compare our results with any Iranian studies. The seroprevalence rate estimated in the present study (34.2%) was higher than estimates from the USA, such as Georgia (8.6% [weighted seroprevalence]) [ 32 ], and Cincinnati Ohio (12.9% [unweighted seroprevalence]) [ 33 ], Denmark (4.0% [test-performance adjusted seroprevalence]) [ 34 ], India (24.1% [weighted and test-performance adjusted seroprevalence]) [ 22 ], Sierra Leone (2.6% [weighted seroprevalence]) [ 35 ], and South Africa (27% [test-performance adjusted seroprevalence]) [ 36 ], which could be partly attributed to the fact that the onset of the COVID-19 epidemic in Iran was earlier than the given countries, leading to longer exposure of Iranian population to the virus and a higher risk of the infection.…”

Section: Discussionmentioning

confidence: 97%

“…The sample size was calculated based on the estimated COVID-19 prevalence of 14.2% [ 9 ], a relative estimation error of 10%, considering a 5% precision, a non-response rate of 10%, and a design effect (Deff) of 1.75 to adjust for the nature of sampling by the following form:…”

Section: Methodsmentioning

confidence: 99%

Seroprevalence of SARS-CoV-2 antibody among urban Iranian population: findings from the second large population-based cross-sectional study

et al. 2022

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Background The first large serosurvey in Iran found a SARS-CoV-2 antibody seroprevalence of 17.1% among the general population in the first wave of the epidemic by April, 2020. The purpose of the current study was to assess the seroprevalence of COVID-19 infection among Iranian general population after the third wave of the disease. Methods This population-based cross-sectional study was conducted on 7411 individuals aged ≥10 years old in 16 cities across 15 provinces in Iran between January and March, 2021. We randomly sampled individuals registered in the Iranian electronic health record system based on their national identification numbers and invited them by telephone to a healthcare center for data collection. Presence of SARS-CoV-2-specific IgG and IgM antibodies was assessed using the SARS-CoV-2 ELISA kits. The participants were also asked about their recent COVID-19-related symptoms, including cough, fever, chills, sore throat, headache, dyspnea, diarrhea, anosmia, conjunctivitis, weakness, myalgia, arthralgia, altered level of consciousness, and chest pain. The seroprevalence was estimated after adjustment for population weighting and test performance. Results The overall population-weighted seroprevalence adjusted for test performance was 34.2% (95% CI 31.0-37.3), with an estimated 7,667,874 (95% CI 6,950,412-8,362,915) infected individuals from the 16 cities. The seroprevalence varied between the cities, from the highest estimate in Tabriz (39.2% [95% CI 33.0-45.5]) to the lowest estimate in Kerman (16.0% [95% CI 10.7-21.4]). In the 16 cities studied, 50.9% of the seropositive individuals did not report a history of symptoms suggestive of COVID-19, implying an estimation of 3,902,948 (95% CI 3,537,760-4,256,724) asymptomatic infected individuals. Conclusions Nearly one in three individuals were exposed to SARS-CoV-2 in the studied cities by March 2021. The seroprevalence increased about two-fold between April, 2020, and March, 2021.

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“…These ranges are described in Table 2 . Given uncertainty in the IFR and its impact of the inferred attack rate, we explore two alternative estimates of IFR by age 21 , 53 and conduct model comparison between the two references through comparison against province level estimated seroprevalence data 16 , with seroprevalence assumed to be described by a Binomial distribution. Lastly, to explore if IFR is changing over time, we explore the ratio of model inferred hospitalisations and observed daily hospitalisations against time using a mixed-effects model, controlling for variation between provinces using a random intercept and slope with respect to time.…”

Section: Methodsmentioning

confidence: 99%

A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data

et al. 2022

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The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to reconstruct SARS-CoV-2 transmission dynamics and assess the level of underreporting in infections and deaths. Using weekly all-cause mortality data from Iran, we are able to show a strong agreement between our attack rate estimates and seroprevalence measurements in each province and find significant heterogeneity in the level of exposure across the country with 11 provinces reaching near 100% attack rates. Despite having a young population, our analysis reveals that incorporating limited access to medical services in our model, coupled with undercounting of COVID-19-related deaths, leads to estimates of infection fatality rate in most provinces of Iran that are comparable to high-income countries.

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Prevalence of COVID-19 in Iran: results of the first survey of the Iranian COVID-19 Serological Surveillance programme

Cited by 41 publications

References 12 publications

SARS-CoV-2 antibody seroprevalence in Lebanon: findings from the first nationwide serosurvey

SARS-CoV-2 antibody seroprevalence in Lebanon: findings from the first nationwide serosurvey

Seroprevalence of SARS-CoV-2 antibody among urban Iranian population: findings from the second large population-based cross-sectional study

A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data

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