SARS-CoV-2 Reinfection Rate and Outcomes in Saudi Arabia: A National Retrospective Study

Highlights•

SARS-CoV-2 reinfection estimated at 0.8% over a 20-month follow-up in Saudi Arabia.

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Diabetes, HIV, obesity and working in healthcare were associated with reinfections.

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Two vaccine doses were associated with 87% risk reduction of reinfection.

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Delta-induced immunity may not be sufficient to prevent subsequent infections.

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Prior infection and vaccination confer a strong protection against severe COVID-19.

AbstractBackground

: The characterization of reinfection with SARS-CoV-2 has been a subject of concern and controversy, especially with the surge of infections with highly transmissible variants worldwide.

Methods

: This retrospective national study used comorbidities, vaccination status, SARS-CoV-2 variants of concern (VOC), and demographics data to profile SARS-CoV-2 reinfected participants, defined as having two RT-PCR positive SARS-CoV-2 tests within at least 90 days apart. A multivariate logistic regression model assessed the risk factors of reinfected cases. Two control groups were selected: non-reinfected participants reporting a positive test (control group one) and reporting a negative test (control group two).

Results

: Between March 2020 and December 2021, 4,454 reinfected participants were identified in Saudi Arabia (0.8%, 95% CI 0.7–0.8). The majority (67.3%) were unvaccinated (95% CI 65.9–68.7) and 0.8% (95% CI 0.6–1.1) had severe or fatal SARS-CoV-2 disease. COVID-19 vaccines were 100% effective against mortality in reinfected individuals who received at least one dose while it conferred 61% (odds ratio [OR] 0.4, 95% CI 0.1–1.0) additional protection against severe disease post first dose and 100% post second dose. In the risk factor analysis, reinfection was highly associated with comorbidities such as HIV (OR 2.5, 95% CI 1.3–5.2; p=0.009), obesity (OR 2.3, 95% CI 1.3–3.9; p=0.003), pregnancy (OR 3.2, 95% CI 1.4–7.4; p=0.005), and working in healthcare (OR 6.1, 95% CI 3.1–12.9; p<0.0001). The delta variant (B.1.617.2) was the most frequent VOC among the reinfected cohort.

Conclusions

: This in-depth study of reinfection profile identified risk factors and highlighted the associated SARS-CoV-2 variants. Results showed that natural-acquired immunity to SARS-CoV-2 through multiple reinfections together with vaccine-induced immunity provided substantial protection against severe SARS-CoV-2 disease and mortality.

Keywords

Introduction

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a virus that causes coronavirus disease 2019 (COVID-19), has infected over 430 million people worldwide (743,205 in Saudi Arabia) and resulted in over 6 million deaths (8,993 in Saudi Arabia), as of February 25, 2022. Despite implementing stringent control measures and travel restrictions, COVID-19 continues to circulate globally, and more recently, the resurgence of COVID-19 cases has been observed following the relaxation of lockdown and social distancing procedures as well as the emergence of variants that posed an increased risk to global public health (Tillett et al. 2021).

It was on the 25th of August 2020 that the first case of reinfection after 4.5 months of initial infection was reported (To et al. 2021), which was subsequently followed by additional cases, each with variable symptom severity on reinfection, from India, the Netherlands, Belgium, and Ecuador (Gupta et al. 2021; Prado-Vivar et al. 2020; Van Elslande et al. 2021).These studies have shown that the viral genome in primary infections and secondary reinfections are phylogenetically distinct and belong to different evolutionary lineages, suggesting that the virus strain detected in the second episode is very different from the strain found in the first episode.

As reinfection rate is likely to be a threat to the end of the COVID-19 pandemic, understanding the frequency, duration of protective immunity, clinical impact, and severity of COVID-19 reinfections is essential to predict the course of the pandemic and prepare for future waves. It would also help gain important insights into the pathophysiology of COVID-19 and guide ongoing vaccine development efforts and future public health surveillance policies. Moreover, predicting who is susceptible to being reinfected is critical for risk evaluation assessments (Babiker et al. 2021).

Given the low supply of vaccines at the beginning of the vaccination scheme, one common strategy adopted in many countries (such as in France, Germany, Italy, and Spain) was to provide only one dose of vaccine to previously infected individuals. This approach has been supported by several studies showing that a single SARS-CoV-2 infection enables one to acquire natural immunity (Ebinger et al. 2021; Goel et al. 2021; Wang et al. 2021). Following the successful implementation of BNT162b2 (Pfizer-BioNTech), ChAdOx1/AZD1222 (Oxford/AstraZeneca), and mRNA-1273 (Moderna) vaccination schemas in Saudi Arabia, with over 60 million receiving their first vaccine dose and 23.6 million fully vaccinated with two doses, individuals who have been infected are strongly advised by Weqaya, the Saudi center for disease control and prevention (CDC) (2021), to delay their vaccination until 90 days post-infection. This strategy relies on the notion that an initial SARS-CoV-2 infection provides powerful protection so that only a single dose of vaccine would be sufficient in those cases. Nevertheless, it is debatable whether a prior SARS-CoV-2 infection or receiving vaccination can achieve adequate immunity against symptomatic reinfection (Jain et al. 2021).

Moreover, the surge of delta (B.1.617.2) and more recently omicron (B.1.1.529) variants has raised major concerns regarding the potential decline in vaccine effectiveness (Lopez Bernal et al. 2021; Collie et al. 2022). Largely dominant worldwide, the delta variant has been proven to have increased replication leading to higher viral loads and subsequently greater transmissibility compared to its alpha and beta counterparts (Planas et al. 2021; Sheikh et al. 2021; Vasireddy et al. 2021). Little is known about the sensitivity of emerging variants of concern (VOCs) to the humoral immune response and therefore, reinfected SARS-CoV-2 individuals harboring these variants will be studied in more detail.

Herein we present, to the best of our knowledge, the first study in Saudi Arabia reporting a comprehensive demographical, clinical, and molecular profiling of SARS-CoV-2 multi-reinfected cases in a mass testing and vaccination setting.

Methods

Study Population, Design, and Data Collection

A total of 4,454 reinfected individuals were included in this study over the period from March 01, 2020, to December 01, 2021, constituting the longest national follow-up period. A duration of at least 90 days between two consecutive positive reverse transcription polymerase chain reaction (RT-PCR) test results for SARS-CoV-2 was the criteria used to identify cases with a high risk of suspicion for SARS-CoV-2 reinfections, following guidelines from the US CDC (CDC, 2020a, 2020b). Remarkably, whilst the majority of individuals (4,258) have acquired at least two episodes of SARS-CoV-2 infection within at least 90 days period (denoted as 1x reinfection), very few acquired multiple reinfection episodes, with 196 individuals having suspected three infections (x2 reinfections).

Reinfected patients’ data were extracted electronically from the centralized Saudi ministry of health (MOH) data repositories, including all SARS-CoV-2 RT-PCR results. Precisely, clinical, and demographic characteristics, vaccination status, variant sequencing data, severe disease defined as patients admitted into intensive care unit (ICU), and mortality (with a follow-up until January 30, 2022) were derived for all reinfected cases. Self-reported data obtained from the vaccination program were extracted to learn about the clinical and social characteristics of the cohort (e.g., comorbidities, occupation). This retrospective study was approved by the Institutional Review Board (IRB) committee from the Saudi MOH (IRB Log No. 21-111 M) with a waiver of informed consent.

SARS-CoV-2 Laboratory Testing and Viral Genome Sequencing

Viral genome sequencing was conducted to determine the VOCs associated with reinfections across a subset of SARS-CoV-2 cases, subject to sample availability and whenever it was possible to retrieve both the primary and reinfection swabs. Viral specimens with Ct values ≤30 were selected for sequencing by the public health laboratory, Saudi CDC. Briefly, an amplicon-based enrichment approach was used for whole-genome sequencing (WGS) using the ATOPlex SARS-CoV-2 full-length genome panel, according to the manufacturer's instructions. Paired-end sequencing was performed on the DNBSEQ-G400 MGI platform. Paired reads were trimmed and mapped to SARS-CoV-2 reference genome sequence MN908947.3 using Burrows-Wheeler Aligner (version 0.7.17), followed by variant calling by SAMtools Mpileup and BCFtools. Consensus sequences were generated by BCFtools and assigned to SARS-CoV-2 lineages with Pangolin.

Statistical Analyses

Clinical and demographic characteristics of the reinfected cohort were described with frequency distributions and measures of central tendency. Vaccination status was compared between vaccinated and unvaccinated reinfected individuals based on the number of doses, the type of vaccine administered and the disease severity (intensive care hospitalizations and/or mortality). Risk factor analysis was conducted by investigating the profile of reinfected, primarily infected, and uninfected individuals. Cases are reinfected individuals denoted as 1x reinfection whereas controls are non-reinfected individuals with or without at least one positive RT-PCR (n=4,454 for both control groups), selected from May 20, 2021, to December 01, 2021, to reduce the bias caused by reopening of the country with the surge of variants and fewer restrictions. The first control group was therefore considered participants "at-risk" of reinfection whilst the second control group distinguished reinfected from uninfected individuals. The odds ratios for 20 risk factors associated with reinfection including age, sex, comorbidities, working in healthcare (HCW), health conditions, and vaccination status were retrieved using a multivariate logistic regression model (Supplementary Methods). The accuracy of the model was evaluated using the area under the curve (AUC) against the testing dataset corresponding to all the x2 reinfections cohort (therefore independent of the training dataset, n=196) with a control group (n=196) comprising primary-infected individuals. The model should predict 1 if cases are PCR-positive and 0 if cases are PCR-negative. Statistical significance was determined at a p-value of <0.05. The following statistical analyses tools were used in this study: Python 3.7 with the packages NumPy (version 1.19.2), Pandas (version 1.1.3), SciPy (version 1.5.2), and statsmodels (version 0.12.1); R with the packages glmnet (version 4.1.1), pROC (version 1.18.0), and forestplot (version 2.0.1).

Results

Demographic and Clinical Features of SARS-CoV-2 Multi-Reinfected Cases

To elucidate the frequency and characteristics of SARS-CoV-2 reinfections among our cohort, 4,454 COVID-19 reinfected cases were collected retrospectively, where 63.7% (n=2,712) of x1 reinfected and 68.9% (n=135) of x2 reinfected individuals were male and surprisingly young, falling in the (26-35 year) age group, with the median age of onset being 32 and 29 years old respectively, as presented in Table 1. The time lapses between each consecutive SARS-CoV-2 infection episode varied considerably, ranging from 90 to 600 days. In our cohort, over 60% of x1 reinfected cases (n=2,819) had longer disease intervals, between 200 and 600 days (Table 1). Notably, out of the whole cohort, approximately 22% (n=960) variant sequencing data were collected, as shown in Table 1, corresponding to those who arrived from overseas as a result of reopening the Saudi borders in May 2021. The majority (88.2%; n=847) of these reinfected individuals harbored delta (B.1.617.2) variants and delta plus (AY.1) with K417N mutations, followed by beta variants (5.1%; n=49). Indeed, delta variants started spreading profusely and uncontrollably from July 2021 onwards and could potentially explain the sudden surge in COVID-19 cases in Saudi and reinfection frequency over the summer period of 2021.

Table 1Demographic and clinical characteristics of COVID-19 multi-reinfected individuals.

Our observation of vaccination and the incidence of reinfection showed that whilst more than 65% of x1 reinfected individuals were unvaccinated (n=2,823), only 2.3% (n=96) received two doses of vaccination before the reinfection, where about 60% of cases received their first doses from BNT162b2 (Pfizer-BioNTech) and 40% from ChAdOx1 (AstraZeneca) (Supplementary Table 1). Similarly, 62% of second vaccine doses were administered by BNT162b2 (Pfizer-BioNTech), 30% by ChAdOx1 (AstraZeneca), and only 8% by mRNA-1273 (Moderna). The average time interval between vaccination and subsequent infection ranged from 36 to 72 days (Supplementary Table 1). Remarkably, out of the 957×1 reinfected individuals with variant sequencing data collected, approximately 42.5% (n=407) were vaccinated, the majority (89.9%; n=366) harbored delta variants (Supplementary Table 2).

We further investigated all the vaccinated reinfected individuals, grouped based on their SARS-CoV-2 infection and vaccination journey (Figure 1). We observed that whilst the minority of x1 reinfected individuals (0.3%; n=5) developed a breakthrough infection within an average of 41 days (SD 43; median 22 days IQR [7-63]) following two doses of vaccination and a second infection within an average of 114 days from the first infection, the majority (89.8%; n=1288) had their primary infections and reinfections flanked by the first vaccine dose, with the time interval between first vaccination and secondary infection averaged 73 days (SD 41; median 73 days IQR [37–104]) (Figure 1.A). Conversely, for the x2 reinfected individuals (n=196), only 10.7% (n=21) were vaccinated, with 33.3% (n=7) of individuals infected for the third time within an average of 45 days post the second dose (Figure 1.B).

Figure 1. Timeline showing all the different scenarios of SARS-CoV-2 reinfection and vaccination journey.

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These scenarios were given across different groups of x1 reinfected (A) and x2 reinfected (B) vaccinated individuals, whereby the average time interval between each infection episode (red) and dose of vaccination (blue) is provided in days, regardless of the type of vaccination and severity of symptoms.

COVID-19 Related Comorbidities for Reinfected Cases

We next investigated the association of comorbidities within our cohort to get a better understanding of the population more prone to SARS-CoV-2 reinfection. Among the reinfected cohort studied, we retrieved the comorbidities information from 1,029 patients, corresponding to 23.1% of reinfected individuals. It is worth mentioning that a reinfected individual can experience more than one comorbidity simultaneously. Consistent with previous findings that immunocompromised patients, such as those who received organ transplants (particularly renal transplant) and patients with uncontrolled diabetes mellitus (DM), are at a higher risk of reinfections with SARS-CoV-2 (Belsky et al. 2021), our data showed that diabetes followed by hypertension, obesity and respiratory diseases were the most common comorbidities associated with COVID-19 reinfections among the x1 and x2 reinfected cohort (Table 2).

Table 2The prevalence of comorbidities associated with COVID-19 reinfections, with confirmed clinical admissions and self-reported data.

HIV, Human Immunodeficiency Virus.

Data are No. (%).

COVID-19 Severe Disease and Mortality Rate for Reinfected Cases

To evaluate the association between SARS-CoV-2 reinfections and severe disease, among the x1 reinfected individuals, 31 (0.7%) patients were admitted into ICU; 26 (83.9%) of these cases were unvaccinated whilst five (16.1%) had received their first vaccine doses. All these patients received life support during hospitalization, including invasive mechanical ventilation (76.9%) and the median length of hospital stay was eight days. Similar to non-ICU cases, 50.2% of these x1 reinfected patients in ICU had diabetes, 11.4% had chronic kidney disease, 11% had hypertension and 6.4% had opportunistic bacterial infections. There were only three (1.5%) ICU cases in the x2 reinfection group, all of which were unvaccinated, where two of them were older than 60 years old and two of them had chronic kidney disease. Furthermore, to determine the frequency of mortality rate due to SARS-CoV-2 reinfections, out of the ∼9000 current COVID-19 deaths in Saudi Arabia, four were x1 reinfected cases, all of which were unvaccinated and three of them had comorbidities including hypertension. No death was recorded for the x2 reinfections among our study cohort (Supplementary Table 3). These findings indicate that prior infection confers strong protection against mortality and further reinforces the importance of vaccination to provide immunity against severe COVID-19 and death.

Risk Factors Associated with SARS-CoV-2 Reinfections

Finally, we determined the risk factors contributing to SARS-CoV-2 reinfections by employing a multivariate logistic regression model using x1 reinfection data. The odds ratios (OR) and 95% confidence intervals (CI) were reported for each risk factor (Supplementary Table 4). The x1 reinfected cases were compared against two control groups: non-reinfected individuals reporting a positive test (control group one) (Figure 2.A) and reporting a negative test (control group two) (Figure 2.B).

Figure 2. Multivariate analysis of SARS-CoV-2 reinfection risk factors.

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Forest plots showing the association between risk factors and SARS-CoV-2 reinfections for a set of demographic and clinical variables for both control groups. The squares and horizontal lines represent the odds ratios (OR) for each risk factor and their associated 95% confidence intervals (CI), respectively. An odd ratio larger than 1 means that the exposure to the risk factor increases the reinfection outcome (and vice versa). A. Reinfection cases with primarily infected control group one (blue squares). B. Reinfection cases with non-infected control group two (red squares).

Figure 2. Multivariate analysis of SARS-CoV-2 reinfection risk factors.

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As shown in Figure 2.A, reinfection was largely associated with vaccination status; unvaccinated individuals were approximately two times more likely to be reinfected against primarily infected individuals (OR 2.2, 95% CI 1.7–2.9; pFigure 2.B). Moreover, individuals known to have a compromised immune system, such as pregnant women and individuals taking immunosuppressive drugs, were more likely to get reinfected with an average OR of 5.7 and 2.0 for both control groups, respectively. Interestingly, we observed that working in healthcare was associated with a high-risk score of being reinfected (OR 6.1, 95% CI 3.1–12.9; pIt is worth noting that the ORs for the two control groups were largely consistent throughout, enabling for unbiased risk factors analysis and a risk profile for reinfection (Supplementary Table 4). There were, however, some disparities in our analysis. For example, we did not observe any vaccine protection after the first dose for ChAdOx1 and BNT162b2, which suggests a waning in vaccine protection consistent with published data (Figure 2.B). The predictive power of the multivariate logistic regression model using the x2 reinfection cohort (n=196) as a testing independent dataset was evaluated to be 65% for control group one and 55% for control group two (Figure 3). Such predictive accuracy on new independent data lends stronger support to the results in Figure 2 which depicts several risk factors associated with SARS-CoV-2 reinfection.

Figure 3. Predictive accuracy of the multivariate logistic regression model.

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Prediction model using the x2 reinfection cohort (n=196) against two non-reinfected control groups; the primarily infected individuals depicted in a blue line (control one) and PCR negative individuals shown in a red line (control two). The area under the curve (AUC) score is given for each receiver operating characteristic (ROC) curve.

Discussion

To our knowledge, we presented one of the largest cohorts of multiple reinfections with SARS-CoV-2 with insights into their clinical, demographic characteristics, and outcomes. It is worth noting that this study was conducted over a 20-month follow-up period (March 01, 2020, to December 01, 2021), encompassing three waves of the pandemic, with the third wave associated with the highly transmissible delta variant. All the data were extracted retrospectively with SARS-CoV-2 reinfected individuals meeting the criteria of more than 90 days between each infection episode regardless of their symptoms, thereby reducing any bias in the selection process.

We reported in this study 4,258 1x reinfections and 196×2 reinfections, corresponding to a reinfection rate of 0.8% (95% CI 0.7–0.8; p<0.0001) in Saudi Arabia from the period of March 01, 2020, to December 01, 2021. This is akin to an earlier report on reinfections from our neighboring country, Qatar, which estimated the reinfection rate at 0.7 per 10,000 persons (95% CI 0.6–0.8) (Abu-Raddad et al. 2021d). However, when looking at a large observational study conducted among more than 500,000 people in Denmark in 2020, 0.7% of individuals who tested positive by PCR in early 2020 tested positive again in late 2020 (Hansen et al. 2021). Nevertheless, none of these studies included a follow-up duration of more than a year and most studies were completed prior to the identification of the beta and delta variants (O Murchu et al. 2021). In our study, reinfections occurred within an average of 8.4 months (SD 3.2; median 8.9 months; IQR [5.5–11.1]) following the first infection episode.

Reinfection suggests that the immune response to a primary infection alone was not adequate to provide sufficient protection against secondary infections. However, we reported that the majority of reinfected individuals were unvaccinated with comorbidities. This supports previous findings that antibody levels in natural infection are not high enough without vaccination and that the population known to be immune-deficient will be more prone to reinfection, including HCWs. (Antonelli et al. 2021; Belsky et al. 2021; Overbaugh, 2020). Therefore, to reduce the likelihood of future reinfections, the study suggests targeting this specific vulnerable group for COVID-19 vaccination, even if they have been previously infected with SARS-CoV-2. This is consistent with many studies showing the additional protectivity of vaccines against infection among infected populations (Abu-Raddad et al. 2021a, 2021b; Townsend et al. 2021). Surprisingly, our study cohort consisted of young adults with the majority of reinfected individuals under the age of 30. This could be explained by recent census data from the Saudi general authority for statistics (2021) that more than 70% of the Saudi population are under the age of 30. Overall, we have observed that vaccination reduced the hospitalization and mortality rate within the reinfected individuals. This finding supports CDC recommendations that all eligible persons be offered COVID-19 vaccination, regardless of previous SARS-CoV-2 infection status.

Although our sequencing data is limited, we were still able to describe the association between the recrudescence of reinfected cases in Saudi Arabia and the reopening of the Kingdom coinciding with the emergence of variants, supported by the high prevalence of delta variants in our cohort and the vaccination status among the sequenced subgroup of individuals demonstrating a waning in vaccine protection against SARS-CoV-2 infection. However, we have shown here that severe illness resulting in intensive care hospitalizations and death in reinfected individuals is a rare phenomenon and mainly occurs amongst the unvaccinated group, suggesting acquired protection from multiple episodes of infection as shown by several studies (Abu-Raddad et al. 2021a, 2021c). Multiple reinfections and vaccination, so-called hybrid immunity, should then provide a strong immune protection against severe and fatal diseases, which is reassuring given the frequent resurgence of cases worldwide (Abu-Raddad et al. 2021c; Jeffery-Smith et al. 2021). However, a worrying new variant called omicron (B.1.1.529), first detected in South Africa on November 24, 2021 and later in Saudi Arabia on December 01, 2021, has shown its capability to evade natural and vaccine-induced immunity (Chaguza et al. 2022; Wilhelm et al. 2021). Indeed, reinfections due to omicron have already been reported to be more frequent (Pulliam et al. 2022). Further studies on omicron will be needed although early reports do not indicate more severe disease (Karim and Karim, 2021).

Nevertheless, there remains to be further investigations, such as the risk of reinfection is likely to be related to the antigenic drift of SARS-CoV-2 towards an immunoresistant profile, rather than a decline in acquired immunity, since most cases reported in this study were based on a positive RT-PCR test without genomic sequencing to confirm reinfection. Another source of concern is the resurgence of infections among those vaccinated with three doses (Kuhlmann et al. 2022). Further analysis of third dose individuals with multiple reinfections would be useful to explain the omicron wave observed from December 2021 worldwide.

Authors’ Contributions

All authors were responsible for aspects of the study design, data collection, data analysis, and manuscript writing. MA conceived the study and designed the analysis plan together with MAA, IK, AA, JA, and MAM. IK performed the data collection and analysis with TA and MHQ. MA, AA, IK, and MAM wrote the manuscript. MA, IK, AA, JA, MAM, MH, MAA and EZ contributed to the data interpretation, background literature search and review. AAG and AAB provided variant sequencing data. All authors read, reviewed, and approved the final submitted manuscript. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Data Sharing

The data that support the findings of this study are available at the Saudi Ministry of Health (MOH), but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. We will consider de-identified participant data sharing upon request following publication.

Conflict of Interest Disclosures

The authors declare no conflicts of interest.

Funding Source

This work was supported by the Saudi Ministry of Health (MOH) in Riyadh, Saudi Arabia. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Ethical Approval Statement

This study was approved by the Institutional Review Board (IRB) committee from the Saudi MOH (IRB Log No. 21-111 M) with a waiver of informed consent.

Acknowledgments

This study was supported by the Saudi Ministry of Health (MOH). We would also like to acknowledge our collaborators, Dr. Ahmed Albarrag and Dr. Abdullah Algwizani from the Saudi CDC/Public Health Authority, for providing variant genome sequencing data.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

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Appendix. Supplementary materialsArticle InfoPublication History

Accepted: July 7, 2022

Received in revised form: June 11, 2022

Received: March 30, 2022

Publication stageIn Press Journal Pre-ProofIdentification

DOI: https://doi.org/10.1016/j.ijid.2022.07.025

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INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES