Four years after the first reports of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the Coronavirus disease (COVID-19) pandemic continues to be a global concern, especially due to the risk of emergence of new variants (Pan et al., 2023; Zhu et al., 2020). In most countries, the variant that is currently epidemiologically dominant is the Omicron (Viana et al., 2022; Zhou et al., 2023), which, due to its increased transmissibility and high number of mutations, led to significant increases in the number of infections in 2022 (Li et al., 2021). Omicron variant infections were first observed in China in December 2021 (Viana et al., 2022), and in Shanghai, the spread of the Omicron BA.2 sublineage led to a substantial increase in COVID-19 incidence between February 26 and June 30, 2022 (Chen et al., 2022b).

In December 2022 (Zheng et al., 2023), an important change in the COVID-19 policy in China, namely the end of most social distancing measures and of mass screening activities, was associated with a second surge in SARS-CoV-2 infections in Shanghai. The current circulation of the virus in the Shanghainese population and reports of vaccine fatigue mean that it is important to estimate the protective effect of vaccination against reinfection in this population. In this study, we aimed to quantify the effect of vaccine doses given after a first infection on the risk of subsequent infection. For that, we used data collected during the first Omicron variant wave, when hundreds of thousands of individuals tested real-time polymerase chain reaction (RT-PCR)-positive for SARS-CoV-2 infection (Huang et al., 2023) in Shanghai, of which 275,896 individuals in Pudong District. The fact that the population in Shanghai was mostly SARS-CoV-2 infection naïve before the spread of the Omicron variant provides a unique opportunity to estimate the real-world benefit of post-infection vaccine doses in a population that was first exposed to infection during a relatively short and well-defined time window. We further investigated whether the number of pre-infection vaccination doses modified the protective effect of the post-infection dose against Omicron BA.5 sublineage. To avoid ambiguity in the text, in the following sections, we often refer to vaccine doses given after the initial infection as ‘post-infection vaccination’ or ‘post-infection vaccine dose’.

We aimed to estimate the added value of a vaccine dose given after SARS-CoV-2 infection in individuals who had received COVID-19 vaccination before the emergence of the Omicron variant. Although quantification of the protective effect of post-infection vaccination in individuals who have been both exposed to infection and previously vaccinated is a public health policy priority, as in many settings this group represents a large fraction of the population, studies on this question are often complicated by the variable timing of infection, vaccination, and reinfection. Here, we leveraged the epidemiological history of COVID-19 in Shanghai municipality, where exposure to first and second SARS-CoV-2 infections occurred during well-defined periods of time, and large electronic databases allowed analyses of vaccination and infection history. Our study showed that post-infection vaccination reduced the risk of reinfection with the Omicron variant during a second, large surge of infections in the city. We also assessed the impact of the timing of vaccination relative to the second Omicron variant wave, and presented secondary and sensitivity analyses. This study will be used to guide COVID-19 vaccination policy in the municipality of Shanghai, and have implications for the rest of the country.

In Shanghai, COVID-19 vaccination started in February 2021 for individuals aged between 18 and 59 years, and over the following months, both older residents and children were included in the vaccination program (Huang et al., 2022). By the time of the first surge of Omicron variant infections, less than 70% of Shanghai residents aged 60–79 years had completed a primary vaccination series, and 40% had received a booster dose (Huang et al., 2023). This was the context in which the population in this municipality was exposed to a first large epidemic of SARS-CoV-2 infections. The change in policy in December 2022 that was associated with a significant increase in the number of infections was our primary motivation to study the additional protection afforded by post-infection vaccination. Indeed, although epidemiological studies have been reported on the effect of vaccination against reinfection, primarily in Europe (Nielsen et al., 2022), North America (Bobrovitz et al., 2023), and Middle East (Gazit et al., 2023), there is limited evidence from settings similar to that in Shanghai, where both the infection and vaccination histories, in terms of vaccine types, differ considerably from those in most Western countries. As individuals increasingly question the benefit of getting vaccinated after COVID-19 recovery, evidence generated locally is necessary.

Previous studies have shown that infection alone can result in immune responses that protect against Omicron variant reinfection. For example, a study in Qatar, with a test-negative design, found that an earlier Omicron variant infection provided protection against symptomatic BA.4 or BA.5 reinfection (Altarawneh et al., 2022). There are also different types of evidence that support post-infection vaccination. In Israel, post-infection vaccination protected against reinfection in individuals with no history of pre-infection vaccination (Hammerman et al., 2022), and prior SARS-CoV-2 infection was associated with lower risk for breakthrough infection among individuals receiving the BNT162b2 or mRNA-1273 vaccines in Qatar (Abu-Raddad et al., 2021). Furthermore, a recent cohort study, performed in the US, of previously infected individuals who were unvaccinated at the time of first infection suggest that vaccination after recovery from COVID-19 decreased risk of reinfection by approximately half (Lewis et al., 2022), which was consistent with a case–control study also conducted in the US (Cavanaugh et al., 2021). Although our research question was different from those in these studies, data from Shanghai suggest that post-infection vaccination in individuals who had received at least one dose of SARS-CoV-2 vaccine before infection provides protection against reinfection. We note that while post-infection vaccination was protective for individuals who had received one or two vaccine doses before the first Omicron variant wave, for those individuals who had received three pre-infection vaccine doses, the evidence for a protective effect was limited. A possible explanation relates to the timing of post-infection vaccination: for all individuals with three pre-infection vaccine doses, the post-infection dose was given in December 2022 and, as a few weeks are required for immunologic boosting, the relatively short follow-up might have been insufficient to detect an effect. Similarly, evidence that post-infection vaccination was protective for individuals who had received booster vaccination before the spread of the first Omicron variant wave in Shanghai was limited; the majority (793/810) of these individuals had three doses before first Omicron variant infection.

In a secondary analysis that assessed the impact of the timing of the post-infection vaccination on the estimated effect, we observe that vaccination within 30 and 90 days before the second surge of Omicron variant provided different degrees of protection, consistent with waning of immunity even in individuals with multiple vaccine doses and history of infection (Ferdinands et al., 2022). As the duration of follow-up in our study was relatively short, we were not able to analyze immunity duration over longer periods of time after the start of the second Omicron variant wave. This observation has implications for COVID-19 vaccination programs: for example, under perfectly functioning logistics, it is possible that timing of vaccination campaigns, including for individuals who have been both previously infected and vaccinated, might be optimal if launched immediately after increase in incidence (e.g. linked to a new variant), rather than immediately after the end of a wave of infections.

In our analyses stratified by demographic characteristics, the protective effect of post-infection vaccination was higher among patients who were 60 years of age or older than among younger individuals. As older individuals are more likely to suffer severe disease, including in settings similar to Shanghai (Chen et al., 2022b), this finding suggests that vaccination of individuals in this age group, even after previous infection and vaccination, is beneficial. Similar to the findings of Sotoodeh Ghorbani et al., 2022, we also found that the rate of reinfection in females was lower than in males; however, the protective effect of post-infection vaccination was similar in the two groups.

We also observed greater protection after an Ad5-nCoV post-infection vaccination in individuals who were fully vaccinated before their first SARS-CoV-2 infection compared to post-infection vaccination with other vaccine types. Note however that not all post-infection doses were of the same type of pre-infection vaccine doses. Another stratified analysis revealed that the protective effect of additional doses was different in individuals who had asymptomatic presentations of the first infection versus those who had symptomatic disease (aHR 0.80 [0.74, 0.87] and 1.01 [0.78, 1.29]). This could be related to different immune responses after infections with different severities. Indeed, reduced antibody response after the initial SARS-CoV-2 infection has been associated with incidence of reinfections. For example, in the study by Islamoglu et al., 2021, it was observed that antibody responses against SARS-CoV-2 were protective against COVID-19 reinfection. Consistently, in the Republic of Korea, CD4⁺ T-cell responses tended to be greater in patients who had severe disease (Kang et al., 2021). In agreement with these studies, that had different designs, our analysis suggests that individuals who had severe or critical COVID-19 had a lower risk of reinfection compared to those who were asymptomatic (see Table 1). Note that individuals who were asymptomatic and those with mild symptoms during the first infection had comparable rates of reinfection. However, individuals with unknown disease severity during the first infection had a higher reinfection rate compared to those with documented clinical severity.

Strengths of our study include: the well-defined timing of first infections and reinfections in Shanghai, linked to the two Omicron variant waves; detailed information on vaccination based on a citywide system; mass screening for SARS-CoV-2 infections during the first Omicron variant surge; free testing during the second Omicron variant wave. Furthermore, to prevent immortal time bias, a common problem in epidemiological studies where treatment/exposure assignment is not aligned with the start of follow-up, we performed survival analysis that used a time varying exposure variable. The insights from our study are also likely generalizable to similar urban settings facing distinct waves of SARS-CoV-2 infections and that adopted the same vaccine types. However, our study also has limitations. First, information on key variables, such as occupation, household registration, clinical severity during the first infection, was missing for a non-negligible fraction of the study population. Although in the primary analysis we performed adjustment for likely confounders, and in the secondary analysis we used propensity score matching, as in other observational studies, we cannot rule out the possibility of residual confounding, which in this context could be related to comorbidities that might affect both the decision to vaccinate after infection and risk of reinfection. Differences in healthcare-seeking behavior could also bias case ascertainment between post-infection vaccinated and unvaccinated individuals (Yung et al., 2023). Although we restricted the study population to individuals who had received at least one pre-infection vaccination, which might have led to a higher degree of homogeneity in healthcare-seeking behavior compared to that in the total population, it is possible that this bias might have affected our estimates. For example: individuals who were more health conscious might have been more likely to receive post-infection vaccination and also more likely to seek medical care or testing when reinfected, and this would have biased results toward the null; it is, however, also conceivable that these individuals were more likely to avoid contact with potentially infectious persons, which could have biased results in the opposite direction. Finally, data on the severity of infections during the second wave were not available, which prevented analyses of clinical outcomes other than infections (e.g. COVID-19-related hospitalization or death). Although some previous studies (Magen et al., 2022; Nasreen et al., 2022; Sacco et al., 2022) estimated similar or higher vaccine effectiveness against severe outcomes compared to outcomes that presumably include both milder and severe presentations, this pattern was not observed in all studies. Epidemiologists and public health officials who will use our results to define vaccination policy should thus take into account the fact that our analysis does not capture all benefits of post-infection vaccinations.

Due to restrictions on data that may potentially reveal identifiable or sensitive patient information, and in accordance with a confidentiality agreement with the Pudong New Area Center for Disease Control and Prevention in Shanghai, the original datasets used and/or analyzed in this study are not publicly available. However, the data that support the findings of this study can be requested for non-commercial purposes by interested researchers. Access to the data is subject to approval by the Ethical Review Committee of the Pudong New Area Center for Disease Control and Prevention in Shanghai, which will then provide the data directly to researchers who fulfill the criteria for access to confidential data. The application process does not require the submission of a project proposal but does require a detailed description of the researcher's identity, the intended use of the data, the purpose of the study, and a signed data confidentiality agreement to safeguard the personal information of patients. Requests for data access should be directed to the Ethical Committee at masterdpf@163.com, who serve as the data custodians. The code utilized for data analysis and graph plotting is included in Source code 1. The anonymized case reinfection data can be accessed at https://doi.org/10.5061/dryad.rfj6q57ks.

1. 1. Yao Y
   2. Zheng B

   (2024) Dryad Digital Repository

   COVID-19 reinfection data on individuals diagnosed with their first SARS-CoV-2 infection.

   https://doi.org/10.5061/dryad.rfj6q57ks

1. 1. Abu-Raddad LJ
   2. Chemaitelly H
   3. Ayoub HH
   4. Yassine HM
   5. Benslimane FM
   6. Al Khatib HA
   7. Tang P
   8. Hasan MR
   9. Coyle P
   10. Al Kanaani Z
   11. Al Kuwari E
   12. Jeremijenko A
   13. Kaleeckal AH
   14. Latif AN
   15. Shaik RM
   16. Abdul Rahim HF
   17. Nasrallah GK
   18. Al Kuwari MG
   19. Butt AA
   20. Al Romaihi HE
   21. Al-Thani MH
   22. Al Khal A
   23. Bertollini R

   (2021) Association of prior SARS-CoV-2 infection with risk of breakthrough infection following mRNA vaccination in Qatar

   JAMA 326:1930–1939.

   https://doi.org/10.1001/jama.2021.19623

   • PubMed
   • Google Scholar
2. 1. Altarawneh HN
   2. Chemaitelly H
   3. Ayoub HH
   4. Hasan MR
   5. Coyle P
   6. Yassine HM
   7. Al-Khatib HA
   8. Smatti MK
   9. Al-Kanaani Z
   10. Al-Kuwari E
   11. Jeremijenko A
   12. Kaleeckal AH
   13. Latif AN
   14. Shaik RM
   15. Abdul-Rahim HF
   16. Nasrallah GK
   17. Al-Kuwari MG
   18. Butt AA
   19. Al-Romaihi HE
   20. Al-Thani MH
   21. Al-Khal A
   22. Bertollini R
   23. Tang P
   24. Abu-Raddad LJ

   (2022) Protective effect of previous SARS-CoV-2 infection against omicron BA.4 and BA.5 subvariants

   The New England Journal of Medicine 387:1620–1622.

   https://doi.org/10.1056/NEJMc2209306

   • PubMed
   • Google Scholar
3. 1. Bobrovitz N
   2. Ware H
   3. Ma X
   4. Li Z
   5. Hosseini R
   6. Cao C
   7. Selemon A
   8. Whelan M
   9. Premji Z
   10. Issa H
   11. Cheng B
   12. Abu Raddad LJ
   13. Buckeridge DL
   14. Van Kerkhove MD
   15. Piechotta V
   16. Higdon MM
   17. Wilder-Smith A
   18. Bergeri I
   19. Feikin DR
   20. Arora RK
   21. Patel MK
   22. Subissi L

   (2023) Protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against the omicron variant and severe disease: a systematic review and meta-regression

   The Lancet. Infectious Diseases 23:556–567.

   https://doi.org/10.1016/S1473-3099(22)00801-5

   • PubMed
   • Google Scholar
4. 1. Cavanaugh AM
   2. Spicer KB
   3. Thoroughman D
   4. Glick C
   5. Winter K

   (2021) Reduced risk of reinfection with SARS-CoV-2 after COVID-19 vaccination - kentucky, May-June 2021

   MMWR. Morbidity and Mortality Weekly Report 70:1081–1083.

   https://doi.org/10.15585/mmwr.mm7032e1

   • PubMed
   • Google Scholar
5. 1. Chen Z
   2. Deng X
   3. Fang L
   4. Sun K
   5. Wu Y
   6. Che T
   7. Zou J
   8. Cai J
   9. Liu H
   10. Wang Y
   11. Wang T
   12. Tian Y
   13. Zheng N
   14. Yan X
   15. Sun R
   16. Xu X
   17. Zhou X
   18. Ge S
   19. Liang Y
   20. Yi L
   21. Yang J
   22. Zhang J
   23. Ajelli M
   24. Yu H

   (2022a) Epidemiological characteristics and transmission dynamics of the outbreak caused by the SARS-CoV-2 Omicron variant in Shanghai, China: A descriptive study

   The Lancet Regional Health - Western Pacific 29:100592.

   https://doi.org/10.1016/j.lanwpc.2022.100592

   • Google Scholar
6. 1. Chen X
   2. Yan X
   3. Sun K
   4. Zheng N
   5. Sun R
   6. Zhou J
   7. Deng X
   8. Zhuang T
   9. Cai J
   10. Zhang J
   11. Ajelli M
   12. Yu H

   (2022b) Estimation of disease burden and clinical severity of COVID-19 caused by Omicron BA.2 in Shanghai, February-June 2022

   Emerging Microbes & Infections 11:2800–2807.

   https://doi.org/10.1080/22221751.2022.2128435

   • PubMed
   • Google Scholar
7. 1. Ferdinands JM
   2. Rao S
   3. Dixon BE
   4. Mitchell PK
   5. DeSilva MB
   6. Irving SA
   7. Lewis N
   8. Natarajan K
   9. Stenehjem E
   10. Grannis SJ
   11. Han J
   12. McEvoy C
   13. Ong TC
   14. Naleway AL
   15. Reese SE
   16. Embi PJ
   17. Dascomb K
   18. Klein NP
   19. Griggs EP
   20. Liao I-C
   21. Yang D-H
   22. Fadel WF
   23. Grisel N
   24. Goddard K
   25. Patel P
   26. Murthy K
   27. Birch R
   28. Valvi NR
   29. Arndorfer J
   30. Zerbo O
   31. Dickerson M
   32. Raiyani C
   33. Williams J
   34. Bozio CH
   35. Blanton L
   36. Link-Gelles R
   37. Barron MA
   38. Gaglani M
   39. Thompson MG
   40. Fireman B

   (2022) Waning of vaccine effectiveness against moderate and severe covid-19 among adults in the US from the VISION network: test negative, case-control study

   BMJ 379:e072141.

   https://doi.org/10.1136/bmj-2022-072141

   • PubMed
   • Google Scholar
8. 1. Gazit S
   2. Saciuk Y
   3. Perez G
   4. Peretz A
   5. Ben-Tov A
   6. Stuart EA
   7. Patalon T

   (2023) Hybrid immunity against reinfection with SARS-CoV-2 following a previous SARS-CoV-2 infection and single dose of the BNT162b2 vaccine in children and adolescents: a target trial emulation

   The Lancet. Microbe 4:e495–e505.

   https://doi.org/10.1016/S2666-5247(23)00103-9

   • PubMed
   • Google Scholar
9. 1. Ge Y
   2. Martinez L
   3. Sun S
   4. Chen Z
   5. Zhang F
   6. Li F
   7. Sun W
   8. Chen E
   9. Pan J
   10. Li C
   11. Sun J
   12. Handel A
   13. Ling F
   14. Shen Y

   (2021) Covid-19 transmission dynamics among close contacts of index patients with covid-19: a population-based cohort study in zhejiang province, China

   JAMA Internal Medicine 181:1343–1350.

   https://doi.org/10.1001/jamainternmed.2021.4686

   • PubMed
   • Google Scholar
10. 1. Hammerman A
    2. Sergienko R
    3. Friger M
    4. Beckenstein T
    5. Peretz A
    6. Netzer D
    7. Yaron S
    8. Arbel R

    (2022) Effectiveness of the BNT162b2 vaccine after recovery from Covid-19

    New England Journal of Medicine 386:1221–1229.

    https://doi.org/10.1056/NEJMoa2119497

    • Google Scholar
11. 1. Hernán MA
    2. Sauer BC
    3. Hernández-Díaz S
    4. Platt R
    5. Shrier I

    (2016) Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses

    Journal of Clinical Epidemiology 79:70–75.

    https://doi.org/10.1016/j.jclinepi.2016.04.014

    • PubMed
    • Google Scholar
12. 1. Huang Z
    2. Xu S
    3. Liu J
    4. Wu L
    5. Qiu J
    6. Wang N
    7. Ren J
    8. Li Z
    9. Guo X
    10. Tao F
    11. Chen J
    12. Lu D
    13. Sun X
    14. Wang W

    (2022) Effectiveness of inactivated and Ad5-nCoV COVID-19 vaccines against SARS-CoV-2 Omicron BA. 2 variant infection, severe illness, and death

    BMC Medicine 20:400.

    https://doi.org/10.1186/s12916-022-02606-8

    • PubMed
    • Google Scholar
13. 1. Huang Z
    2. Xu S
    3. Liu J
    4. Wu L
    5. Qiu J
    6. Wang N
    7. Ren J
    8. Li Z
    9. Guo X
    10. Tao F
    11. Chen J
    12. Lu D
    13. Wang Y
    14. Li J
    15. Sun X
    16. Wang W

    (2023) Effectiveness of inactivated COVID-19 vaccines among older adults in Shanghai: retrospective cohort study

    Nature Communications 14:2009.

    https://doi.org/10.1038/s41467-023-37673-9

    • Google Scholar
14. 1. Islamoglu MS
    2. Cengiz M
    3. Uysal BB
    4. Ikitimur H
    5. Ozdemir Z
    6. Karamehmetoglu A
    7. Akbulut AE
    8. Bakdur AN
    9. Ozdemir A
    10. Kayıkcıoglu H
    11. Ozdemir H
    12. Uces R
    13. Ersoy S
    14. Yavuzer S

    (2021)

    Relationship between antibody levels and SARS-Cov-2 reinfection

    Annals of Clinical and Laboratory Science 51:750–755.

    • PubMed
    • Google Scholar
15. Website

    1. Jian Y

    (2023) No more free PCR tests in Shanghai from Sunday

    Accessed January 20, 2024.

    https://www.shine.cn/covid19/2301064857/
16. 1. Kang CK
    2. Kim M
    3. Lee S
    4. Kim G
    5. Choe PG
    6. Park WB
    7. Kim NJ
    8. Lee C-H
    9. Kim IS
    10. Jung K
    11. Lee D-S
    12. Shin HM
    13. Kim H-R
    14. Oh M-D

    (2021) Longitudinal analysis of human memory t-cell response according to the severity of illness up to 8 months after severe acute respiratory syndrome coronavirus 2 infection

    The Journal of Infectious Diseases 224:39–48.

    https://doi.org/10.1093/infdis/jiab159

    • PubMed
    • Google Scholar
17. 1. Lewis N
    2. Chambers LC
    3. Chu HT
    4. Fortnam T
    5. De Vito R
    6. Gargano LM
    7. Chan PA
    8. McDonald J
    9. Hogan JW

    (2022) Effectiveness associated with vaccination after covid-19 recovery in preventing reinfection

    JAMA Network Open 5:e2223917.

    https://doi.org/10.1001/jamanetworkopen.2022.23917

    • PubMed
    • Google Scholar
18. 1. Li J
    2. Lai S
    3. Gao GF
    4. Shi W

    (2021) The emergence, genomic diversity and global spread of SARS-CoV-2

    Nature 600:408–418.

    https://doi.org/10.1038/s41586-021-04188-6

    • Google Scholar
19. 1. Magen O
    2. Waxman JG
    3. Makov-Assif M
    4. Vered R
    5. Dicker D
    6. Hernán MA
    7. Lipsitch M
    8. Reis BY
    9. Balicer RD
    10. Dagan N

    (2022) Fourth dose of BNT162b2 mRNA Covid-19 vaccine in a nationwide setting

    The New England Journal of Medicine 386:1603–1614.

    https://doi.org/10.1056/NEJMoa2201688

    • PubMed
    • Google Scholar
20. 1. Nasreen S
    2. Chung H
    3. He S
    4. Brown KA
    5. Gubbay JB
    6. Buchan SA
    7. Fell DB
    8. Austin PC
    9. Schwartz KL
    10. Sundaram ME
    11. Calzavara A
    12. Chen B
    13. Tadrous M
    14. Wilson K
    15. Wilson SE
    16. Kwong JC
    17. Canadian Immunization Research Network (CIRN) Provincial Collaborative Network (PCN) Investigators

    (2022) Effectiveness of COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe outcomes with variants of concern in Ontario

    Nature Microbiology 7:379–385.

    https://doi.org/10.1038/s41564-021-01053-0

    • PubMed
    • Google Scholar
21. Website

    1. National Center for Immunization and Respiratory Diseases (U.S.). Division of Viral Diseases

    (2020) Investigative criteria for suspected cases of SARS-CoV-2 reinfection (ICR)

    Accessed August 7, 2023.

    https://stacks.cdc.gov/view/cdc/96072
22. 1. Nielsen KF
    2. Moustsen-Helms IR
    3. Schelde AB
    4. Gram MA
    5. Emborg H-D
    6. Nielsen J
    7. Hansen CH
    8. Andersen MA
    9. Meaidi M
    10. Wohlfahrt J
    11. Valentiner-Branth P

    (2022) Vaccine effectiveness against SARS-CoV-2 reinfection during periods of Alpha, Delta, or Omicron dominance: A Danish nationwide study

    PLOS Medicine 19:e1004037.

    https://doi.org/10.1371/journal.pmed.1004037

    • PubMed
    • Google Scholar
23. 1. Pan Y
    2. Wang L
    3. Feng Z
    4. Xu H
    5. Li F
    6. Shen Y
    7. Zhang D
    8. Liu WJ
    9. Gao GF
    10. Wang Q

    (2023) Characterisation of SARS-CoV-2 variants in Beijing during 2022: an epidemiological and phylogenetic analysis

    Lancet 401:664–672.

    https://doi.org/10.1016/S0140-6736(23)00129-0

    • PubMed
    • Google Scholar
24. 1. Sacco C
    2. Del Manso M
    3. Mateo-Urdiales A
    4. Rota MC
    5. Petrone D
    6. Riccardo F
    7. Bella A
    8. Siddu A
    9. Battilomo S
    10. Proietti V
    11. Popoli P
    12. Menniti Ippolito F
    13. Palamara AT
    14. Brusaferro S
    15. Rezza G
    16. Pezzotti P
    17. Fabiani M
    18. Italian National COVID-19 Integrated Surveillance System and the Italian COVID-19 vaccines registry

    (2022) Effectiveness of BNT162b2 vaccine against SARS-CoV-2 infection and severe COVID-19 in children aged 5-11 years in Italy: a retrospective analysis of January-April, 2022

    Lancet 400:97–103.

    https://doi.org/10.1016/S0140-6736(22)01185-0

    • PubMed
    • Google Scholar
25. 1. Sotoodeh Ghorbani S
    2. Taherpour N
    3. Bayat S
    4. Ghajari H
    5. Mohseni P
    6. Hashemi Nazari SS

    (2022) Epidemiologic characteristics of cases with reinfection, recurrence, and hospital readmission due to COVID-19: A systematic review and meta-analysis

    Journal of Medical Virology 94:44–53.

    https://doi.org/10.1002/jmv.27281

    • PubMed
    • Google Scholar
26. 1. Ueno M
    2. Komeda K
    3. Kosaka H
    4. Nakai T
    5. Nomi T
    6. Iida H
    7. Tanaka S
    8. Ikoma H
    9. Matsuda K
    10. Hirokawa F
    11. Matsumoto M
    12. Hokuto D
    13. Mori H
    14. Morimura R
    15. Kaibori M
    16. Yamaue H
    17. Kubo S

    (2021) Prognostic impact of neoadjuvant chemotherapy in patients with synchronous colorectal liver metastasis: A propensity score matching comparative study

    International Journal of Surgery 94:106106.

    https://doi.org/10.1016/j.ijsu.2021.106106

    • PubMed
    • Google Scholar
27. 1. Viana R
    2. Moyo S
    3. Amoako DG
    4. Tegally H
    5. Scheepers C
    6. Althaus CL
    7. Anyaneji UJ
    8. Bester PA
    9. Boni MF
    10. Chand M
    11. Choga WT
    12. Colquhoun R
    13. Davids M
    14. Deforche K
    15. Doolabh D
    16. du Plessis L
    17. Engelbrecht S
    18. Everatt J
    19. Giandhari J
    20. Giovanetti M
    21. Hardie D
    22. Hill V
    23. Hsiao N-Y
    24. Iranzadeh A
    25. Ismail A
    26. Joseph C
    27. Joseph R
    28. Koopile L
    29. Kosakovsky Pond SL
    30. Kraemer MUG
    31. Kuate-Lere L
    32. Laguda-Akingba O
    33. Lesetedi-Mafoko O
    34. Lessells RJ
    35. Lockman S
    36. Lucaci AG
    37. Maharaj A
    38. Mahlangu B
    39. Maponga T
    40. Mahlakwane K
    41. Makatini Z
    42. Marais G
    43. Maruapula D
    44. Masupu K
    45. Matshaba M
    46. Mayaphi S
    47. Mbhele N
    48. Mbulawa MB
    49. Mendes A
    50. Mlisana K
    51. Mnguni A
    52. Mohale T
    53. Moir M
    54. Moruisi K
    55. Mosepele M
    56. Motsatsi G
    57. Motswaledi MS
    58. Mphoyakgosi T
    59. Msomi N
    60. Mwangi PN
    61. Naidoo Y
    62. Ntuli N
    63. Nyaga M
    64. Olubayo L
    65. Pillay S
    66. Radibe B
    67. Ramphal Y
    68. Ramphal U
    69. San JE
    70. Scott L
    71. Shapiro R
    72. Singh L
    73. Smith-Lawrence P
    74. Stevens W
    75. Strydom A
    76. Subramoney K
    77. Tebeila N
    78. Tshiabuila D
    79. Tsui J
    80. van Wyk S
    81. Weaver S
    82. Wibmer CK
    83. Wilkinson E
    84. Wolter N
    85. Zarebski AE
    86. Zuze B
    87. Goedhals D
    88. Preiser W
    89. Treurnicht F
    90. Venter M
    91. Williamson C
    92. Pybus OG
    93. Bhiman J
    94. Glass A
    95. Martin DP
    96. Rambaut A
    97. Gaseitsiwe S
    98. von Gottberg A
    99. de Oliveira T

    (2022) Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

    Nature 603:679–686.

    https://doi.org/10.1038/s41586-022-04411-y

    • PubMed
    • Google Scholar
28. 1. Wu J
    2. Li Q
    3. Silver Tarimo C
    4. Wang M
    5. Gu J
    6. Wei W
    7. Ma M
    8. Zhao L
    9. Mu Z
    10. Miao Y

    (2021) COVID-19 vaccine hesitancy among chinese population: a large-scale national study

    Frontiers in Immunology 12:781161.

    https://doi.org/10.3389/fimmu.2021.781161

    • Google Scholar
29. Website

    1. Xinguang T

    (2017) Pudong new area builds full-coverage medical service chain

    Accessed August 7, 2023.

    https://enshanghaiacademy.shu.edu.cn/info/1013/2339.htm
30. 1. Ye L
    2. Li WF
    3. Shao J
    4. Xu Z
    5. Ju J
    6. Xu H

    (2022) Fighting Omicron epidemic in China: Real-world big data from Fangcang shelter hospital during the outbreak in Shanghai 2022

    The Journal of Infection 85:436–480.

    https://doi.org/10.1016/j.jinf.2022.07.006

    • PubMed
    • Google Scholar
31. 1. Yung CF
    2. Pang D
    3. Kam KQ
    4. Lye DC
    5. Ong B
    6. Chong CY
    7. Tan KB

    (2023) BNT162b2 vaccine protection against omicron and effect of previous infection variant and vaccination sequence among children and adolescents in Singapore: a population-based cohort study

    The Lancet Child & Adolescent Health 7:463–470.

    https://doi.org/10.1016/S2352-4642(23)00101-3

    • Google Scholar
32. 1. Zhang X
    2. Zhang W
    3. Chen S

    (2022) Shanghai’s life-saving efforts against the current omicron wave of the COVID-19 pandemic

    Lancet 399:2011–2012.

    https://doi.org/10.1016/S0140-6736(22)00838-8

    • PubMed
    • Google Scholar
33. 1. Zheng L
    2. Liu S
    3. Lu F

    (2023) Impact of National Omicron Outbreak at the end of 2022 on the future outlook of COVID-19 in China

    Emerging Microbes & Infections 12:2191738.

    https://doi.org/10.1080/22221751.2023.2191738

    • PubMed
    • Google Scholar
34. 1. Zhou Y
    2. Zhi H
    3. Teng Y

    (2023) The outbreak of SARS-CoV-2 Omicron lineages, immune escape, and vaccine effectivity

    Journal of Medical Virology 95:e28138.

    https://doi.org/10.1002/jmv.28138

    • PubMed
    • Google Scholar
35. 1. Zhu N
    2. Zhang D
    3. Wang W
    4. Li X
    5. Yang B
    6. Song J
    7. Zhao X
    8. Huang B
    9. Shi W
    10. Lu R
    11. Niu P
    12. Zhan F
    13. Ma X
    14. Wang D
    15. Xu W
    16. Wu G
    17. Gao GF
    18. Tan W
    19. China Novel Coronavirus Investigating and Research Team

    (2020) A novel coronavirus from patients with pneumonia in China, 2019

    The New England Journal of Medicine 382:727–733.

    https://doi.org/10.1056/NEJMoa2001017

    • PubMed
    • Google Scholar

Author details

1. Bo Zheng

   Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China

   Contribution

   Conceptualization, Formal analysis, Methodology, Visualization, Writing – original draft

   Contributed equally with

   Bronner P Gonçalves and Pengfei Deng

   Competing interests

   No competing interests declared

2. Bronner P Gonçalves

   Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Guildford, United Kingdom

   Contribution

   Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Bo Zheng and Pengfei Deng

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3329-6050

3. Pengfei Deng

   Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China

   Contribution

   Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft

   Contributed equally with

   Bo Zheng and Bronner P Gonçalves

   Competing interests

   No competing interests declared

4. Weibing Wang

   1. Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
   2. Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China

   Contribution

   Funding acquisition, Resources, Supervision, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4497-5251

5. Jie Tian

   Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China

   Contribution

   Conceptualization, Software, Visualization

   Competing interests

   No competing interests declared

6. Xueyao Liang

   Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China

   Contribution

   Conceptualization, Data curation

   Competing interests

   No competing interests declared

7. Ye Yao

   School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China

   Contribution

   Data curation, Resources, Validation, Writing – review and editing

   For correspondence

   yyao@fudan.edu.cn

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0878-8942

8. Caoyi Xue

   Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China

   Contribution

   Data curation, Funding acquisition, Resources, Validation, Writing – review and editing

   For correspondence

   xuecaoyi83@163.com

   Competing interests

   No competing interests declared

• 584

  views

• 64

  downloads

• 0

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.