Introduction

Coronavirus disease 2019 (COVID-19) has caused substantial morbidity and mortality worldwide. Since the beginning of the pandemic, various measures, including non-pharmaceutical measures, have been taken to prevent the spread of the disease, and vaccination has played a key role in preventing the development of severe cases and transmission [1,2,3]. However, the effectiveness of the vaccine has been shown to diminish over time, and there is a demand for repeated vaccination [4,5,6,7]. As the human and object resources required for vaccination are problematic, a rationale for repeated vaccination is needed. Identifying patients at high risk of reinfection is critical for the development of future infection prevention strategies, but detailed data on the rate of reinfection in the community and which factors increase the risk of reinfection are limited [2, 8,9,10,11,12,13]. The number of suspected and confirmed reinfections is increasing as the pandemic continues, and it is important to determine what measures should be taken to create a society that can coexist with COVID-19.

In this study, we analysed population-based notification records to explore the characteristics of and risk factors for reinfection.

Methods

Study design and data collection

This was a retrospective cohort study that analysed notification records of all COVID-19 cases in citizens in Kyoto City, Kyoto, Japan, who were diagnosed by COVID-19 testing from 30 January 2020 to 15 April 2022. Kyoto City is the seventh largest city located in the Kansai region of Japan with 1.4 million people. Characteristics, including age, sex, symptoms at the diagnosis, occupation, risk factors for severe infection, route of infection and the date and types of vaccination for all individuals, were collected and analysed. In this study, the risk factors for severe infection included malignancy, chronic obstructive pulmonary disease, chronic kidney disease, hypertension, diabetes mellitus, hyperlipidaemia, obesity and a history of smoking, which are the criteria for risk factors in the national notification system in Japan. The route of infection for each case is investigated by the local health care centre, and records are kept in the centre. Cases were divided into 4 age groups: 0–17, 18–39, 40–59 and over 60 years. Notification records with incomplete information on either age or the date of infection were excluded from the analysis. The major SARS-CoV-2 lineages in this research were defined as the variants’ predominance which was identified by the national genomic surveillance of the Ministry of Health, Labours and Welfare, Japan. (https://www.mhlw.go.jp/stf/seisakunitsuite/newpage_00061.html, accessed as of 30 Apr 2022).

The Ethics Committee of Kyoto University Graduate School and Faculty of Medicine approved this study (R2379) and waived the need to obtain informed consent from each patient.

Vaccination, testing and infection control policy in Kyoto City during the study period

During the study period, two mRNA vaccines (BNT 162b2 [Pfizer/BioNtech] and mRNA-1273 [Moderna]) were distributed in Kyoto City. At the end of 2021, when the Omicron variant (BA.1) started to spread, 82.5% of the eligible population had received 2 vaccine doses. In the 18–39 years age group, 73.1% of individuals had received the 2nd vaccine dose, and in the 40–59 years age group, 82.3% of individuals had received the 2nd vaccine dose; in those over 60 years old, 93% had received the 2nd vaccine dose, and booster shots were started in December 2021. Vaccines for children aged 5 to 11 years old were finally approved in January 2022; thus, the vaccination rate in this group was less than 3% during the study period.

In Kyoto City, COVID-19 tests are performed in medical institutions for symptomatic patients. The local health care centre in Kyoto City actively traced and tested close contacts to identify asymptomatic cases. Diagnosis of COVID-19 was made by physicians, and all cases were reported and recorded in the electrical database in a local health care centre. Wearing face mask in public was strongly recommended and large-scale events were restricted during the study period in Kyoto City.

Definition of reinfection and vaccination status

In this study, reinfection was defined as a positive PCR test or a rapid antigen test for COVID-19 at least 90 days after the first positive test irrespective of symptoms [14] (https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-2021/), with follow-up until death or 30 April 2022. In addition, subgroup analysis was performed using Yahav et al.’s definition of reinfection, in which involves clinical recurrence of symptoms compatible with COVID-19, to exclude continuous viral shedding cases [15]. Individuals were considered vaccinated if an interval of at least 14 days had elapsed between the date of the vaccination and the COVID-19 test date to allow induction of an immune response.

Statistical analysis

Group comparisons were made using the X2 test, Fisher’s exact test and the Wilcoxon test. Variables with probability values < .05, as shown by univariate analysis, were included in the multiple regression analysis. The odds ratios and their respective 95% confidence intervals were computed as estimates of relative risk. A P value of < .05 was considered statistically significant. All statistical analyses were completed using JMP® software version 16.0 (SAS Institute Inc., Cary, NC, USA).

Results

Between 30 January 2020 and 15 April 2022, we identified 107,475 patients who received ≥ 1 positive COVID-19 result, which was 7.3% of the entire population in Kyoto City, Kyoto, Japan. Of these, 709 unique patients met the criteria for reinfection (0.66% of patients with a positive result, 0.05% of the entire population) (Fig. 1). As shown in Fig. 2, as high as 77% of the total cohort was infected during the Omicron surge (BA.1 and BA.2).

Fig. 1
figure 1

Number of notification records and proportion of reinfected cases by age group. Between 30 January 2020 and 15 April 2022, we identified 107,475 patients who received ≥ 1 positive COVID-19 result. Of these, 709 unique patients met the criteria for reinfection (0.66% of patients with a positive result; 0.05% of the entire population)

Full size image
Fig. 2
figure 2

Trends of reinfection cases by the initial timing (wave) and the number of COVID-19 cases in Kyoto City. Major lineages of SARS-CoV-2 in Kyoto City during the study period are shown at the top of the figure. The first recorded COVID-19 reinfection case was reported in January 2021. Since then, the number of COVID-19 reinfections remained low until the Omicron surge in the community

Full size image

The first recorded COVID-19 reinfection case was reported in January 2021. Since then, the number of COVID-19 reinfection cases was small until the Delta and Omicron surge in the community (Fig. 2). The mean duration (± standard deviation) between 2 positive tests was 259.5 ± 126 days, ranging from 97 to 729 days.

Risk factors for reinfection

The demographic and clinical characteristics of patients who developed reinfection versus those who did not are shown in Table 1, and the reinfection rate by occupation is shown in Supplementary Table 1. The age group with the highest reinfection rate was the 18–39 years age group, followed by the 40–59 years age group. Out of the 709 reinfected individuals, fifty-four were asymptomatic at the second infection. The occupations with the highest reinfection rates were workers in the construction and manufacturing industry, followed by the hospitality industry, which includes restaurant workers (Table 2). Interestingly, the reinfection rate was not high among healthcare workers and employees of elder-care facilities. In addition, the reinfection rate for those at risk of severe disease was only 0.20%. According to the multivariate analysis, the 18–39 years age group was more likely to be reinfected, compared to the 0–17 years age group (4.97; 95% CI: 3.84–6.43), followed by the 40–59 years age group (OR: 2.83; 95% CI: 2.10–3.83) (Table 3). Other risk factors identified included employment in the construction and manufacturing industry or the hospitality industry as well as individuals asymptomatic during the initial infection. In contrast, 2 doses of vaccination and exhibiting risk factors for severe infection were protective factors against reinfection. These tendencies were also confirmed in subgroup analysis that included only data from symptomatic cases (Supplementary Table 2).

Table 1 Demographic and clinical characteristics of reinfected individuals and the total cohort
Full size table
Table 2 Univariate analysis of risk factors for reinfection
Full size table
Table 3 Multivariate analysis of risk factors for reinfection
Full size table

The most common infection route of the initial infection was “friends or acquaintances,” but for reinfection, most of the infection routes were “unknown” (Supplementary Table 3).

Discussion

This study provides original data on possible rates of reinfection with COVID-19 in Japan for the first time, generated from a population-based comprehensive notification database of COVID-19 cases in Kyoto City, Kyoto, Japan. While possible reinfection was a rare event (less than 1% of positive cases) during the study period, the frequency increased after the spread of Omicron (BA.1). Such a trend was also observed in France [16] and could be explained by the waning of post-infection and post-vaccination immunity. Moreover, the unknown infection route may reflect the immune escape characteristics of Omicron or an increase in the rate of community transmission, which may promote reinfection. This pattern is consistent with our results and other reports worldwide and a worrisome observation regarding the further emergence of new variants [17,18,19,20].

Regarding age group, reinfection was more common in the 18–39 years age group, followed by the 40–59 years age group, which are regarded as the most socially active age groups. In previous reports, the relationship between age and susceptibility to reinfection has shown conflicting results [2, 21]. For example, according to Bastard et al., the number of reinfection cases among people aged 18 to 40 years was significantly higher, even though 2 vaccination doses were administered to over 90% of the cohort [16]. In contrast, a population surveillance study in Denmark revealed that age ≥ 65 years was identified as a significant risk factor for reinfection [2]. In terms of occupation, the risk of reinfection was high in workers in the construction and manufacturing industry and workers in the hospitality industry, both of whom frequently have face-to-face interactions with other workers and customers. In contrast, employees in health care facilities and elder-care facilities, where clusters often occur, were not at high risk of reinfection, inconsistent with previous reports [16, 22, 23]. Vaccination is aggressively promoted for health care workers and nursing facility staff in Japan; thus, high vaccination rates may have lowered reinfection in these populations, despite a high risk of exposure.

Risk of reinfection is affected by immunity, exposure and compliance with prevention measures [24, 25]. In our cohort, relatively younger age and unvaccinated status were risk factors for reinfection. We assume that the elderly generations in our cohort were protected because vaccination of the elderly is being promoted in Kyoto City, and as of April 2022, vaccination coverage among those aged 60 years and older was over 93% [3]. Furthermore, elderly people tend to have comorbidities, which may result in changes in behaviour to prevent reinfection. Detailed analyses of the risks for reinfection in terms of occupation are rare; therefore, further studies are needed to ensure the generalizability of these observations. However, considering the risk factors for reinfection identified in this study, age group, occupation, vaccination status and comorbidities might be related to behaviours that prevent reinfection. We suppose that surviving the COVID-19 pandemic requires the expert guidance of behavioural science as well as knowledge of infection control. Regarding the former, low vaccination coverage among the reinfected cases in our cohort confirmed the urgent need to encourage vaccination, especially among those who work in high-risk service industries.

The current study has its strengths. Our study population includes the largest number of individuals with COVID-19 for whom the risk of reinfection has been examined in Japan. We identified suspected reinfections in a range of care settings, during periods of high and low community transmission and with a long follow-up period. In this descriptive study, detailed personal information about patients’ occupations and routes of infection were also obtained, which are valuable in establishing further infection control measures.

However, our study also has limitations. First, without any genome sequencing data to confirm reinfection, the study relied on a repeated positive COVID-19 test in a previously infected patient as a marker of reinfection. Some positive test results could represent persistent viral shedding from the index infection, including in patients with impaired immunity (< 5% of the cohort), although our requirement of a minimum 90-day interval between positive PCR results likely minimized this possibility. Furthermore, patients reinfected by a different strain before the 90-day cut-off were also missed. Second, most cases were infected during the Omicron wave. The total number of infected cases dramatically increased, which might have resulted in the increase in reinfection cases irrespective of vaccination status, age and occupation. Third, some information was missing from the electronic database; these missing values are expressed as “unknown” in our tables. Missing information may have been due to incomplete input of data by physicians or manual procedures in the database system. Missing data might partially affect the results of this study.

Conclusion

The data presented herein on possible COVID-19 reinfection provide valuable information about reinfection characteristics and frequency over time. Overall, these results are encouraging from a public health perspective, as the burden of symptomatic and/or acutely ill patients with suspected reinfection was low. However, variants of concern and the possible waning of immunity over time might lead to a higher burden of reinfection in the future. As it appears very unlikely that COVID-19 will be eradicated, monitoring the frequency of and risk factors for reinfection is critical for establishing policies for preventing infection.