Abstract
Background
During the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) such as social distancing, lockdowns and enhanced hygiene led to a decrease in respiratory pathogens. However, as NPIs were relaxed, a resurgence in several respiratory pathogens was observed including one local Chlamydia pneumoniae outbreak in Switzerland, prompting the need for a better understanding of C. pneumoniae epidemiology.
Aim
To assess temporal and geographical variations in C. pneumoniae detection before, during and after the COVID-19 pandemic.
Methods
Data on C. pneumoniae PCR detection ratios (number of positive tests/ total number of tests) across pre-pandemic (2018–2019), pandemic (2020–2022) and post-pandemic (2023) periods were collected via a global survey disseminated through various professional networks.
Results
C. pneumoniae detection ratios were analysed across 28 sites (27 in Europe, one in Taiwan) in 2023 (Dataset A, n = 172,223 tests) and 20 sites from 2018 to 2023 (Dataset B, n = 693,106 tests). Twenty-seven sites were laboratories (hospital or clinical) and one a surveillance system (Denmark). A significant decrease in detection ratios was observed during the pandemic period (from 1.05% to 0.23%, p < 0.001). In 2023, detection ratios increased to 0.28% (p < 0.002). Notable regional variations were found, with statistically significant increases in detection ratios at six sites located in Switzerland and Slovenia, where ratios ranged from 0.52% to 3.25%.
Discussion
The study highlights how NPIs influenced C. pneumoniae epidemiology, with reduced detection during the pandemic and partial resurgence afterwards. Regional variations suggest differing NPI impacts and underscore the need for continued surveillance.
Keywords: pneumonia, bronchitis, asthma, outbreak, upsurge, PCR, molecular diagnosis
Key public health message.
What did you want to address in this study and why?
Chlamydia pneumoniae is a bacterium that causes respiratory tract infections. Due to observed shifts in patterns of some respiratory pathogens following the lifting of non-pharmaceutical interventions (NPIs), such as lockdowns and social distancing, after the COVID-19 pandemic, we wanted to observe patterns of C. pneumoniae. Furthermore, a local outbreak in Switzerland in late 2023 raised concerns about a potential global resurgence.
What have we learnt from this study?
We found that C. pneumoniae detection was reduced during the pandemic period (2020–2022) when NPIs were in place and partially rebounded in 2023, although with a delay, after most NPIs were lifted. Regional variations in resurgence patterns suggest differing impacts of NPIs on pathogen transmission and indicate the potential for future resurgences.
What are the implications of your findings for public health?
Ongoing surveillance is crucial for understanding the long-term epidemiological trends of C. pneumoniae and preparing for potential resurgences in countries that have not experienced any increase in detection rates.
Introduction
During the first 2 years of the COVID-19 pandemic (2020–2022), the incidence of many pathogens, including respiratory pathogens such as influenza viruses, respiratory syncytial virus (RSV) and Mycoplasma pneumoniae, decreased. This was due to the implementation of non-pharmaceutical interventions (NPIs) such as social distancing, lockdowns, school closures, stay-at-home orders, mask-wearing and enhanced hygiene practices, including widespread use of hydroalcoholic solutions for hand hygiene [1-4]. However, as these NPIs were lifted, a global resurgence of these pathogens was observed, with some, such as M. pneumoniae and Streptococcus pyogenes, showing infection rates even higher than those seen before the COVID-19 pandemic [5-7]. This resurgence was likely due to decreased levels of specific immunity against airborne pathogens.
Chlamydia pneumoniae is an intracellular bacterium responsible for respiratory infection ranging from upper respiratory tract infection to bronchitis and pneumonia [8]. In general, pneumonia is typically mild with a favourable prognosis and low mortality rate (< 2%) [9,10]. However, severe cases may occasionally be observed resulting in hospitalisation, sporadically accompanied by complications such as pleural effusion or empyema, and the need for intensive care [9,11,12]. Seroepidemiological studies indicate that primary infections are rare in children under 5 years old in temperate regions [13]. When primary infection occurs in adults, it can lead to more severe clinical outcomes compared with reinfection [11]. There is a strong association between C. pneumoniae and asthma initiation, persistence, exacerbation and treatment resistance [14,15]. C. pneumoniae infections can be treated with either macrolides, fluoroquinolones or doxycycline [16]. In recent years, molecular diagnosis has emerged as the best technique to diagnose acute infections caused by this intracellular bacterium, showing excellent sensitivity and specificity [17-19]. The pathogen DNA can be found in abundance in respiratory samples such as nasopharyngeal swabs, sputa or bronchial aspirates and broncho-alveolar lavages. Multiplexing has also proven to be efficient, as coinfections frequently occur (and as bystander, allows the monitoring of epidemiological trends of various respiratory pathogens) [20-22]. Serology demonstrates lower sensitivity than PCR testing, particularly if the sample is taken during the serological window (when patients are infected but have not yet produced detectable levels of antibodies) or if convalescent serum is unavailable. It also demonstrates lower specificity due to cross-reactivity and the influence of past infections, and considerable variability between different serological assays has been reported compared with PCR [23,24]. In addition, cell culture is not suitable for routine diagnosis.
In the past several years, a few C. pneumoniae outbreaks have been reported, such as in a prison in Texas, United States in 2013 (52 cases identified) and in South Korea in 2016 where 19 cases were reported in children [10,25]. From our literature search, we did not find reports of outbreaks occurring between 2016 and 2022. To our knowledge, the most recent outbreak to be reported occurred in Lausanne, Switzerland in late 2023 after the COVID-19 pandemic [26]. Between October and December 2023, routine epidemiologic surveillance at Lausanne University Hospital in Switzerland revealed an unexpected rise in C. pneumoniae PCR detection ratios, reaching 3.61% overall and peaking at 6.66% in October, with a total of 28 patients identified. These figures contrast with the hospital’s historical rates over the past decade, which typically ranged from 0% to 0.75%. This unexpected surge prompted us to conduct a multicentric epidemiological study on C. pneumoniae infections to determine whether similar patterns are emerging globally, particularly in the context of the observed resurgence of other pathogens following the COVID-19 pandemic. Thus, we, through the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Mycoplasma and Chlamydia Infections (ESGMAC), performed a survey aiming to assess temporal and geographical variations in C. pneumoniae detection before, during and after the COVID-19 pandemic.
Methods
Survey development and dissemination
A structured survey was adapted from the survey developed for the study of M. pneumoniae detection ratios following established guidelines for survey research by Patrick Meyer-Sauteur et al. [2]. It was adapted to collect data on C. pneumoniae detection ratios. The survey included four sections: (i) participant details, (ii) information about the testing laboratory and region, (iii) detailed information on the testing method for C. pneumoniae detection (including technique, product and manufacturer or reference), (iv) C. pneumoniae molecular testing data (total tests, positive tests, positive tests by month, proportion of children/adolescents under 18 years and females of any age). The survey was conducted in English and hosted on the SurveyMonkey online platform (SurveyMonkey Inc, San Mateo, California, US, www.surveymonkey.com). Additional details of the survey are provided in the Supplementary material.
The survey was disseminated worldwide to hospital laboratories, infectious disease specialists and members of national surveillance systems (with contacts in Europe more represented) through various channels, including ESCMID study groups (ESGMAC, the ESCMID Study Group for Genomics and Molecular Diagnostics (ESGMD), the ESCMID Study Group for Epidemiological Markers (ESGEM)) and national infectious diseases and microbiology societies via newsletters or email distribution lists, social media (Swiss Society for Microbiology) and direct in-person contact by some authors (FT and GG). The survey was advertised during an ESGMAC webinar in January 2024. Potential participants were contacted and provided with a summary of the study and a link to the online survey. Participation was on a voluntary basis and without any financial compensation. Consent for data publication and participant listing was obtained on the first page of the questionnaire. The survey was launched on 1 December 2023, with reminders sent to potential participants via email after 6 and 10 weeks. We closed the survey on 31 March 2024. Each entry, originating from a laboratory (hospital or clinical) or a surveillance system was considered a site.
Data quality control
Each entry was carefully checked for (i) data completeness, (ii) data origin, and (iii) molecular diagnostics method. Furthermore, we assessed each entry to prevent data duplication by thoroughly checking for similarities in the introduced numbers.
Case definition
We included detection ratios from PCR tests only, due to improved sensitivity and specificity of PCR compared to serology. Each positive PCR result was considered a potential case. We analysed PCR detection ratios (number of positive tests divided by the total number of tests over a defined period) in this study, not incidence or prevalence as we could not control for multiple testing of the same individual.
Statistical analysis
To analyse the results, three periods were defined: 2018–2019 (the situation before the COVID-19 pandemic, also referred as the pre-pandemic period), 2020–2022 (the situation during COVID-19 pandemic, the pandemic period) and 2023 (after the COVID-19 pandemic, also referred as the post-pandemic period). The proportion of children/adolescents and females were calculated as follows: number of tests performed on children/adolescents younger than 18 years old, or in females, respectively, divided by the total number of tests performed. For global comparison, detection ratios between the periods were analysed using the Wilcoxon signed rank test with continuity correction (data were indicated as paired). Significance was set to p < 0.05. Then, the three periods were analysed pairwise using contingency tables with Fisher’s exact test in R software version 4.2.2 [27]. Detection ratios were analysed as no denominator was available to calculate incidence rates. P value significance level was adapted according to Benjamini-Hochberg correction for multiple testing [28].
Results
Study population and detection methods
Following the dissemination of the study, 49 survey answers (entries) were received. Of these, a total of 21 entries were excluded: 11 due to missing numeric data despite reminders, eight were duplicate entries from the same individuals or sites, and two used serology instead of PCR. Two datasets were obtained: Dataset A, comprising 28 sites in 2023, and Dataset B, covering 20 sites from 2018 to 2023 (Figure 1).
Figure 1.
Study dissemination and data collection leading to two complete datasets, encompassing sites in Europe and Taiwan, 1 November 2023–31 March 2024
UN: United Nations.
Societies: ESCMID: European Society for Clinical Microbiology and Infectious Diseases study groups; ESGMAC: ESCMID study group for Mycoplasma and Chlamydia Infections; ESGMD: ESCMID Study Group for Genomics and Molecular Diagnostics; ESGEM: ESCMID Study Group for Epidemiological Markers; the Swiss Society for Microbiology.
These two datasets were used for further analysis. Most sites were in Europe (n = 27), with one site in Asia (n = 1) (Table 1).
In total, Dataset A (2023 only) included data from 172,223 PCR tests. Among these, 18.7% of the tests were from patients under 18 years old, and 50.0% were from females (more details can be found in Supplementary Table S2). Two and five sites, respectively, did not specify the proportion of children/adolescents under 18 years and females of any age and were therefore excluded from our calculations, resulting in 171,497 tests used to assess PCR detection ratios for patients under 18 years old and 166,564 tests for female patients. Dataset B, covering the period from 2018 to 2023, included a total of 693,106 PCR tests. For sites that provided demographic data in Dataset B (n = 672,558), 14.9% of the tests were for children/adolescents and 50.2% were for females. Overall C. pneumoniae detection ratio was 0.31% (± 2 standard deviations (SD): 0.05%) in Dataset A and 0.47% (± 2SD: 0.13%) in Dataset B. Children/adolescents represented 56.4% of positive detections in Dataset A, and 37.1% in Dataset B. Female representation among positive detection was balanced in both datasets (50.0% for A and 52.0% for B).
Of the 28 sites, one site (Denmark) employed a mixed approach, combining in-house and commercial PCR methods. Denmark was considered a site although it provided data from the Danish Microbiological Database (MiBa) [29], which aggregated PCR test results from 10 different microbiological laboratories, all using commercially available PCR-based platforms (Table 1). Denmark was the only site providing country-wide data. Of the other 27 testing sites, seven exclusively used in-house PCR tests, while 19 relied on various commercially available PCR-based platforms.
Table 1. Laboratory type, location, method and specific Chlamydia pneumoniae PCR technique or manufacturer used and dataset attribution for the study, 27 European sites and Taiwan, 1 November 2023–31 March 2024.
| Entry number | Laboratory type | City | Country | Methods | Technique or manufacturer | Dataset |
|---|---|---|---|---|---|---|
| 1 | Hospital or clinical laboratory | Antwerp | Belgium | Singleplex PCR | In-house [31] | A + B |
| 2 | Hospital or clinical laboratory | Prague | Czechia | Multiplex PCR | Atypical Pneumonia 8-well (AusDiagnostics) | A + B |
| 3 | National data (MiBa) | Copenhagen | Denmark | PCR | Various commercial assays | A + B |
| 4 | Hospital or clinical laboratory | Helsinki | Finland | Multiplex PCR | In-house | A + B |
| 5 | Hospital or clinical laboratory | Marseille | France | Multiplex and single qPCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux), Fast Track Diagnosis respiratory pathogene (Siemens healthineers), in-house qPCR | A + B |
| 6 | Hospital or clinical laboratory | Bordeaux | France | Singleplex PCR | In-house | A + B |
| 7 | Hospital or clinical laboratory | 's-Hertogenbosch | Netherlands | PCR | In-house | A + B |
| 8 | Hospital or clinical laboratory | Sittard-Geleen | Netherlands | Multiplex PCR | In-house | A |
| 9 | Hospital or clinical laboratory | Rotterdam | Netherlands | Multiplex PCR | Allplex PneumoBacter Assay (Seegene) | A |
| 10 | Hospital or clinical laboratory | Arnhem | Netherlands | Multiplex PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) | A |
| 11 | Hospital or clinical laboratory | Ljubljana | Slovenia | Multiplex PCR | Chla/Myco pneumo R-GENE (bioMérieux) | A + B |
| 12 | Hospital or clinical laboratory | Bilbao | Spain | Multiplex PCR | Allplex Respiratory Panel 4 (Seegene) | A |
| 13 | Hospital or clinical laboratory | Barcelona | Spain | Multiplex PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) | A + B |
| 14 | Hospital or clinical laboratory | Santa Cruz de Tenerife | Spain | Multiplex PCR | Allplex Respiratory panel 4 (Seegene) | A + B |
| 15 | Hospital or clinical laboratory | Buchs | Switzerland | Multiplex PCR | Allplex Respiratory Panel 4 (Seegene) and Filmarray Respiratory Panel 2.1 plus (bioMérieux) | A + B |
| 16 | Hospital or clinical laboratory | Niederwangen | Switzerland | Singleplex PCR | In-house [17] | A + B |
| 17 | Hospital or clinical laboratory | Zurich | Switzerland | Multiplex PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) | A |
| 18 | Hospital or clinical laboratory | Chur | Switzerland | Multiplex PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) | A |
| 19 | Hospital or clinical laboratory | Lausanne | Switzerland | In-house duplex PCR | In-house [19] | A + B |
| 20 | Hospital or clinical laboratory | La Chaux-de-Fonds | Switzerland | Multiplex PCR | QIASTAT (QIAGEN), Filmarray Respiratory Panel 2.1 plus (bioMérieux), RIDAGENE CAP Bac (r-biopharm) | A + B |
| 21 | Hospital or clinical laboratory | Lucerne | Switzerland | Multiplex PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) | A + B |
| 22 | Hospital or clinical laboratory | Basel | Switzerland | Multiplex PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) and Allplex PneumoBacter Assay (Seegene) | A |
| 23 | Hospital or clinical laboratory | Lausanne | Switzerland | Multiplex and single PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) and CHP/ISEX/025 (Geneproof) | A |
| 24 | Hospital or clinical laboratory | Bioggio | Switzerland | Multiplex and single PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) and CHP/ISEX/025 (Geneproof) | A + B |
| 25 | Hospital or clinical laboratory | Lucerne | Switzerland | Multiplex and single PCR | Filmarray Respiratory Panel 2.1 plus (bioMérieux) and CHP/ISEX/025 (Geneproof) | A + B |
| 26 | Hospital or clinical laboratory | Zurich | Switzerland | Multiplex PCR | Respiratory multiplex Lightmix Kit (Roche) | A + B |
| 27 | Hospital or clinical laboratory | Geneva | Switzerland | Duplex real-time PCR | BD-MAX AP-2 (Becton Dickinson) | A + B |
| 28 | Hospital or clinical laboratory | Taichung | Taiwan | Multiplex PCR | QIASTAT (QIAGEN) | A + B |
MiBa: Danish Microbiological Database.
Significant decrease in cases during the pandemic period
An overall decrease in detection ratios was seen between the pre-pandemic and pandemic periods (Figure 2, Figure 3).
Figure 2.
Monthly variation in PCR detection ratios of Chlamydia pneumoniae, 19 European sites and Taiwan, 2018–2023
Dataset B was used to generate this graph.
Figure 3.
Annual PCR detection ratios for Chlamydia pneumoniae, 19 European sites and Taiwan, 2018–2023
Dataset B was used to generate this graph. Denmark was the only country providing country-wide data. Numbers between parentheses are the total number of tests performed.
From an overall detection ratio of 1.05% (± 2SD: 0.22%) during the pre-pandemic period, this dropped significantly to 0.23% (± 2SD: 0.04%) during the pandemic period (p ≤ 0.001). However, some sites continued to see the circulation of C. pneumoniae, particularly in France (Marseille), Belgium (Antwerp) and in two sites in Switzerland (Geneva and Niederwangen) (Table 2). At the site level, a significant decrease in detection ratios was only seen in Denmark, Finland, Slovenia and Switzerland (4 of 9 sites), although detection ratios decreased without reaching statistical significance or stayed at 0% in all the other sites except the Belgian site (Table 2, Figure 3).
Table 2. PCR detection ratios for Chlamydia pneumoniae and detailed numbers of samples over the three study periods for Dataset B, 19 European sites and Taiwan, 2018–2023.
| Country | City | PCR detection ratios (%) | Number of samples (2018–2019) | Number of samples (2020–2022) | Number of samples (2023) | p value | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Pre-pandemic period 2018–2019 |
Pandemic period 2020–2022 |
Post-pandemic period 2023 |
Positive | Negative | Positive | Negative | Positive | Negative | 2018–2019 vs 2020–2022 | 2018–2019 vs 2023 | 2020–2022 vs 2023 | ||
| Belgium | Antwerp | 0.28 | 0.31 | 0.00 | 2 | 713 | 3 | 959 | 0 | 114 | 1.00 | 1.00 | 1.00 |
| Czechia | Prague | 0.15 | 0.02 | 0.04 | 5 | 3,417 | 1 | 6,453 | 1 | 2,819 | 0.02 | 0.23 | 0.52 |
| Denmark | Copenhagen | 1.20 | 0.26 | 0.23 | 1,898 | 155,757 | 643 | 246,310 | 257 | 110,849 | < 0.01 | < 0.01 | 0.11 |
| Finland | Helsinki | 0.85 | 0.13 | 0.25 | 11 | 1,287 | 2 | 1,489 | 1 | 397 | < 0.01 | 0.32 | 0.51 |
| France | Marseille | 0.23 | 0.18 | 0.09 | 22 | 9,465 | 86 | 46,724 | 23 | 25,424 | 0.31 | < 0.01 | < 0.01 |
| France | Bordeaux | 0.00 | 0.00 | 0.13 | 0 | 913 | 0 | 1,591 | 1 | 751 | 1.00 | 0.45 | 0.32 |
| Netherlands | s-Hertogenbosch | 0.00 | 0.00 | 0.43 | 0 | 491 | 0 | 1,199 | 3 | 693 | 1.00 | 0.27 | 0.05 |
| Slovenia | Ljubljana | 0.75 | 0.22 | 0.81 | 27 | 3,567 | 11 | 5,015 | 19 | 2,315 | < 0.01 | 0.88 | < 0.01 |
| Spain | Barcelona | 0.00 | 0.00 | 1.22 | 0 | 101 | 0 | 266 | 1 | 81 | 1.00 | 0.45 | 0.24 |
| Spain | Santa Cruz de Tenerife | 0.13 | 0.06 | 0.00 | 1 | 758 | 1 | 1,660 | 0 | 1,027 | 0.53 | 0.43 | 1.00 |
| Switzerland | Lucerne | 3.19 | 0.00 | 0.48 | 3 | 91 | 0 | 358 | 1 | 206 | < 0.01 | 0.10 | 0.37 |
| Switzerland | Buchs | 0.39 | 0.04 | 1.46 | 12 | 3,088 | 2 | 5,513 | 51 | 3,440 | < 0.01 | < 0.01 | < 0.01 |
| Switzerland | Niederwangen | 0.90 | 0.62 | 3.25 | 2 | 221 | 2 | 321 | 10 | 298 | 1.00 | 0.08 | 0.02 |
| Switzerland | Lausanne | 0.40 | 0.00 | 1.95 | 7 | 1,730 | 0 | 2,880 | 29 | 1,456 | < 0.01 | < 0.01 | < 0.01 |
| Switzerland | La Chaux-de-Fonds | 0.66 | 0.21 | 0.66 | 6 | 897 | 1 | 476 | 21 | 3,152 | 0.43 | 1.00 | 0.35 |
| Switzerland | Lucerne | 0.15 | 0.00 | 0.84 | 3 | 1,958 | 0 | 3,878 | 16 | 1,894 | 0.04 | < 0.01 | < 0.01 |
| Switzerland | Bioggio | 0.86 | 0.04 | 0.71 | 11 | 1,262 | 1 | 2,597 | 5 | 695 | < 0.01 | 0.80 | < 0.01 |
| Switzerland | Zurich | 0.04 | 0.00 | 0.52 | 1 | 2,375 | 0 | 5,519 | 9 | 1,708 | 0.30 | < 0.01 | < 0.01 |
| Switzerland | Geneva | 0.61 | 0.50 | 0.45 | 19 | 3,088 | 23 | 4,598 | 10 | 2,191 | 0.53 | 0.57 | 1.00 |
| Taiwan | Taichung | 0.00 | 0.00 | 0.08 | 0 | 0 | 0 | 109 | 1 | 1,237 | 1.00 | 1.00 | 1.00 |
Fisher’s exact Test with correction for multiple testing (Benjamini–Hochberg procedure) was used to compare the three periods.
p values in bold indicate statistical significance (p < 0.05).
Four sites located in Taiwan (Taichung), France (Bordeaux), the Netherlands (s-Hertogenbosch) and Spain (Barcelona) reported no cases of C. pneumoniae in the pre-pandemic and pandemic periods, indicating a likely complete absence of C. pneumoniae circulating in the regions where the sites are located. When looking at the monthly detection ratios between 2018 and 2023 (Figure 2), overall ratios were close to 0% between April 2020 and June 2023, with a mean monthly positivity ratio of 0.064% (± 2SD: 0.004%). This decline in detection ratios coincides with the deployment of COVID-19 prevention measures (lockdowns, school closures) (lockdown periods can be found in Supplementary Table S1 and visualized in Supplementary Figure S1).
Epidemiology in the post-pandemic period, 2023
The second half of 2023 was marked by an increase in the overall C. pneumoniae detection ratios (Figure 2), with important variations between countries (Figure 4A and Figure 4B).
Figure 4.
PCR detection ratios for Chlamydia pneumoniae, 27 European sites and Taiwan, 2023
Dataset A was used to generate these figures (raw data and detection rates are available in Supplementary Table S2). Total number of tests are indicated between parentheses. The geographical representation was generated using Bing (Geonames, Microsoft, Open places, OpenStreetMap, TomTom). Denmark was the only site providing country-wide data.
This rebound was observed on the overall data and the detection ratios shifted from a mean of 0.23% (± 2SD: 0.04%) in the pandemic period to 0.28% (± 2SD: 0.04%) in the post-pandemic period (p ≤ 0.002) (Figure 3). When looking at the differences between the sites in the pandemic and post-pandemic periods, statistical significance was only reached in two countries, Switzerland (5/9 sites) and Slovenia (1/1 site), where ratios ranged from 0.52% to 3.25% (Table 2). One site in France (Marseille) had a statistically significant decrease in detection ratios in the post-pandemic compared with the pandemic period. Two sites reported no cases in 2023, in Spain (Santa Cruz de Tenerife) and in Belgium (Antwerp). Several countries continued to experience similar C. pneumoniae detection ratios during and after the pandemic period, namely Denmark, Finland and one site in Switzerland (Geneva).
Differences between the pre-pandemic and post-pandemic periods
Globally, detection ratios in the post-pandemic period remained lower than in the pre-pandemic period (Figure 2, Figure 3), although this difference was not statistically significant (p = 0.65). The differences in detection ratios before and after the pandemic period were statistically significant in six sites. In Denmark and in France, these differences corresponded to a decrease in detection ratios, while in Switzerland (4 sites), there was a statistically significant increase in detection ratios between pre-pandemic and post-pandemic periods.
Discussion
The study reveals significant epidemiological shifts in the detection of C. pneumoniae across various sites, primarily in Europe, during and after the COVID-19 pandemic. The implementation of NPIs such as lockdowns, social distancing, use of facial masks and school closures during the pandemic likely contributed to a marked reduction in the transmission of respiratory pathogens, including C. pneumoniae. This is evidenced by the overall decrease in C. pneumoniae detection ratios observed during the pandemic period, with some sites reporting almost negligible detection ratios during the height of the pandemic. These results align with other studies that have reported a significant decline in other respiratory infections during the same period, likely due to the widespread implementation of public health measures aimed at curbing the spread of severe acute respiratory syndrome coronavirus 2 [1-4]. Since children/adolescents represented only 18.7% and 14.9% in Dataset A and B, respectively, the larger representation of children/adolescents among all the positive tests (56.4% in Dataset A and 37.1% in Dataset B) likely indicates a higher prevalence among children/adolescents.
However, the post-pandemic period, particularly in the second half of 2023, shows a notable rebound in C. pneumoniae detection ratios. This resurgence suggests a possible re-emergence of the pathogen as NPIs were relaxed. The increase in detection ratios was statistically significant in several sites, notably in Switzerland and Slovenia, indicating a potential shift in the epidemiological landscape in the post-pandemic period. Interestingly, while most regions with participating sites showed an increase in detection ratios, a site in France (Marseille) exhibited a statistically significant decrease, suggesting regional variability in how the relaxation of NPIs influenced C. pneumoniae circulation.
The persistently lower detection ratios in the post-pandemic compared with the pre-pandemic period, for example in Denmark and certain sites in France, may indicate lasting effects of the pandemic on pathogen circulation or possibly reflect changes in public behaviour and healthcare practices that might have persisted beyond the immediate pandemic response. For example, sustained improvements in hygiene practices or continued cautious behaviour in public spaces could contribute to these lower ratios. However, the duration of these effects may vary depending on the pathogen, as both Denmark and France already experienced resurgences of M. pneumoniae in 2023 [7,30].
Conversely, the statistically significant increase in detection ratios in several Swiss sites in the post-pandemic period raises questions about the factors contributing to this rebound. Possible explanations could include a combination of factors such as decreased population immunity due to reduced pathogen circulation during the pandemic, changes in healthcare-seeking behaviour or even shifts in diagnostic practices or criteria. The regional differences observed highlight the complexity of the pandemic’s epidemiological impact and underscore the need for ongoing surveillance to monitor the evolution of C. pneumoniae epidemiology, and possibly anticipate rebounds in countries that have not experienced rebounds.
Our study is limited in its geographical representation, as 27 sites are in Europe and only one is in Asia, offering insights only into regions with participating sites. We were not able to obtain data outside Europe and Taiwan. In addition, the number of tests performed varied considerably across sites and countries, limiting the representativeness of the data in some regions. While Denmark provided national data, several countries (Belgium, Czechia, Finland, Slovenia and Taiwan) had only a single participating site. Moreover, the variability in detection methods across sites, with some relying on in-house PCR assays while others use commercial methods, introduces an additional layer of complexity in interpreting these findings. The differences in sensitivity and specificity of these assays could influence detection ratios, potentially contributing to the observed regional differences. Detection ratios may also be impacted by local practices and awareness of the primary-care physician about the different clinical presentation of C. pneumoniae. In addition, variability may also arise from differing policies, such as molecular testing being conducted primarily for inpatients at some sites, while others may extend this testing to outpatients as well. It is also possible that a significant number of C. pneumoniae infections went undetected, as they may cause only asymptomatic or mild illness in a portion of the population. Since this study focused on molecular diagnosis results, further studies combining molecular and serological prevalence data could provide more comprehensive insights.
Conclusion
This study provides insights into the evolving epidemiology of C. pneumoniae in the context of the COVID-19 pandemic. The findings underscore the profound impact of global non-pharmaceutical public health measures on pathogen circulation and highlight the importance of continued surveillance and research to understand the long-term consequences of the pandemic on respiratory pathogens. Further investigation is needed to explore the underlying factors driving the observed regional differences and to assess the potential long-term changes in the epidemiology of C. pneumoniae in the post-pandemic world.
Ethical statement
This study collected aggregated data that contained no specific identifying data and that were collected as part of the routine diagnostics. For the specific site in Slovenia, an approval from the ethical commission was already available for the collection of epidemiological data (The Commission of the Republic of Slovenia for Medical Ethics, 0120-244/2021/3).
Use of artificial intelligence tools
ChatGPT was used to correct and improve the text in terms of spelling and phrasing. All outputs were carefully reviewed afterward.
Acknowledgements
We would like to thank Hege Vangstein Aamot, Michael L. Beeton, Natacha Couto, Jørgen Skov Jensen and Sylvia Bruisten for their help disseminating the study survey.
We would also like to thank the ESCMID Study Group for Mycoplasma and Chlamydia infections (ESGMAC) for allowing networking necessary for such a large collaborative work.
Supplementary Data
Supplementary Data
Authors’ contributions: Study conceptualisation and design: FT and GG. Acquisition of data: SAU, CB, BI, RC, SE, AF, JF, DGMA, DG, EH, MH, FI, DK, CL, RL, CM, VM, PMMS, IM, OO, CO, PD, OP, LPY, MP, MR, KTDT, NW. Analysis and interpretation of data: FT. Writing of the original manuscript draft: FT. All authors contributed to the work, reviewed, and approved the manuscript.
Conflict of interest: None declared.
Funding statement: Not applicable.
Data availability
All data are readily available in the manuscript or the Supplementary material.
References
- 1. Huang QS, Wood T, Jelley L, Jennings T, Jefferies S, Daniells K, et al. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand. Nat Commun. 2021;12(1):1001. 10.1038/s41467-021-21157-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Meyer Sauteur PM, Beeton ML, Uldum SA, Bossuyt N, Vermeulen M, Loens K, et al. ESGMAC–MyCOVID Study Team . Mycoplasma pneumoniae detections before and during the COVID-19 pandemic: results of a global survey, 2017 to 2021. Euro Surveill. 2022;27(19):2100746. 10.2807/1560-7917.ES.2022.27.19.2100746 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Baker RE, Park SW, Yang W, Vecchi GA, Metcalf CJE, Grenfell BT. The impact of COVID-19 nonpharmaceutical interventions on the future dynamics of endemic infections. Proc Natl Acad Sci USA. 2020;117(48):30547-53. 10.1073/pnas.2013182117 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Oster Y, Michael-Gayego A, Rivkin M, Levinson L, Wolf DG, Nir-Paz R. Decreased prevalence rate of respiratory pathogens in hospitalized patients during the COVID-19 pandemic: possible role for public health containment measures? Clin Microbiol Infect. 2021;27(5):811-2. 10.1016/j.cmi.2020.12.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Gouveia C, Bajanca-Lavado MP, Mamede R, Araújo Carvalho A, Rodrigues F, Melo-Cristino J, et al. Sustained increase of paediatric invasive Streptococcus pyogenes infections dominated by M1UK and diverse emm12 isolates, Portugal, September 2022 to May 2023. Euro Surveill. 2023;28(36):2300427. 10.2807/1560-7917.ES.2023.28.36.2300427 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Alcolea-Medina A, Snell LB, Alder C, Charalampous T, Williams TGS, Tan MKI, et al. The ongoing Streptococcus pyogenes (Group A Streptococcus) outbreak in London, United Kingdom, in December 2022: a molecular epidemiology study. Clin Microbiol Infect. 2023;29(7):887-90. 10.1016/j.cmi.2023.03.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Meyer Sauteur PM, Beeton ML, Pereyre S, Bébéar C, Gardette M, Hénin N, et al. Mycoplasma pneumoniae: delayed re-emergence after COVID-19 pandemic restrictions. Lancet Microbe. 2024;5(2):e100-1. 10.1016/S2666-5247(23)00344-0 [DOI] [PubMed] [Google Scholar]
- 8. Tagini F, Puolakkainen M, Greub G, On Behalf Of The Escmid Study Group For Mycoplasma And Chlamydia Infections Esgmac . From coughs to complications: the story of Chlamydia pneumoniae. J Med Microbiol. 2025;74(4):002006. 10.1099/jmm.0.002006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Kauppinen MT, Saikku P, Kujala P, Herva E, Syrjälä H. Clinical picture of community-acquired Chlamydia pneumoniae pneumonia requiring hospital treatment: a comparison between chlamydial and pneumococcal pneumonia. Thorax. 1996;51(2):185-9. 10.1136/thx.51.2.185 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Conklin L, Adjemian J, Loo J, Mandal S, Davis C, Parks S, et al. Investigation of a Chlamydia pneumoniae outbreak in a Federal correctional facility in Texas. Clin Infect Dis. 2013;57(5):639-47. 10.1093/cid/cit357 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Ekman MR, Grayston JT, Visakorpi R, Kleemola M, Kuo CC, Saikku P. An epidemic of infections due to Chlamydia pneumoniae in military conscripts. Clin Infect Dis. 1993;17(3):420-5. 10.1093/clinids/17.3.420 [DOI] [PubMed] [Google Scholar]
- 12. Augenbraun MH, Roblin PM, Mandel LJ, Hammerschlag MR, Schachter J. Chlamydia pneumoniae pneumonia with pleural effusion: diagnosis by culture. Am J Med. 1991;91(4):437-8. 10.1016/0002-9343(91)90165-T [DOI] [PubMed] [Google Scholar]
- 13. Grayston JT, Campbell LA, Kuo CC, Mordhorst CH, Saikku P, Thorn DH, et al. A new respiratory tract pathogen: Chlamydia pneumoniae strain TWAR. J Infect Dis. 1990;161(4):618-25. 10.1093/infdis/161.4.618 [DOI] [PubMed] [Google Scholar]
- 14. Von Hertzen L. Role of persistent infection in the control and severity of asthma: focus on Chlamydia pneumoniae. Eur Respir J. 2002;19(3):546-56. 10.1183/09031936.02.00254402 [DOI] [PubMed] [Google Scholar]
- 15. Von Hertzen L, Vasankari T, Liippo K, Wahlström E, Puolakkainen M. Chlamydia pneumoniae and severity of asthma. Scand J Infect Dis. 2002;34(1):22-7. 10.1080/00365540110077155 [DOI] [PubMed] [Google Scholar]
- 16. Kohlhoff SA, Hammerschlag MR. Treatment of Chlamydial infections: 2014 update. Expert Opin Pharmacother. 2015;16(2):205-12. 10.1517/14656566.2015.999041 [DOI] [PubMed] [Google Scholar]
- 17. Reischl U, Lehn N, Simnacher U, Marre R, Essig A. Rapid and standardized detection of Chlamydia pneumoniae using LightCycler real-time fluorescence PCR. Eur J Clin Microbiol Infect Dis. 2003;22(1):54-7. 10.1007/s10096-002-0858-2 [DOI] [PubMed] [Google Scholar]
- 18. Tondella MLC, Talkington DF, Holloway BP, Dowell SF, Cowley K, Soriano-Gabarro M, et al. Development and evaluation of real-time PCR-based fluorescence assays for detection of Chlamydia pneumoniae. J Clin Microbiol. 2002;40(2):575-83. 10.1128/JCM.40.2.575-583.2002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Opota O, Brouillet R, Greub G, Jaton K. Methods for real-time PCR-based diagnosis of Chlamydia pneumoniae, Chlamydia psittaci, and Chlamydia abortus infections in an opened molecular diagnostic platform. Methods Mol Biol. 2017;1616:171-81. 10.1007/978-1-4939-7037-7_11 [DOI] [PubMed] [Google Scholar]
- 20. Leber AL, Lisby JG, Hansen G, Relich RF, Schneider UV, Granato P, et al. Multicenter evaluation of the QIAstat-Dx respiratory panel for detection of viruses and bacteria in nasopharyngeal swab specimens. J Clin Microbiol. 2020;58(5):e00155-20. 10.1128/JCM.00155-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Murphy CN, Fowler R, Balada-Llasat JM, Carroll A, Stone H, Akerele O, et al. Multicenter evaluation of the BioFire FilmArray pneumonia/pneumonia plus panel for detection and quantification of agents of lower respiratory tract infection. J Clin Microbiol. 2020;58(7):e00128-20. 10.1128/JCM.00128-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Verkooyen RP, Willemse D, Hiep-van Casteren SC, Mousavi Joulandan SA, Snijder RJ, van den Bosch JM, et al. Evaluation of PCR, culture, and serology for diagnosis of Chlamydia pneumoniae respiratory infections. J Clin Microbiol. 1998;36(8):2301-7. 10.1128/JCM.36.8.2301-2307.1998 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Dowell SF, Peeling RW, Boman J, Carlone GM, Fields BS, Guarner J, et al. Standardizing Chlamydia pneumoniae assays: recommendations from the Centers for Disease Control and Prevention (USA) and the Laboratory Centre for Disease Control (Canada). Clin Infect Dis. 2001;33(4):492-503. 10.1086/322632 [DOI] [PubMed] [Google Scholar]
- 24. Tuuminen T, Palomäki P, Paavonen J. The use of serologic tests for the diagnosis of chlamydial infections. J Microbiol Methods. 2000;42(3):265-79. 10.1016/S0167-7012(00)00209-8 [DOI] [PubMed] [Google Scholar]
- 25. Han HY, Moon JU, Rhim JW, Kang HM, Lee SJ, Yang EA. Surge of Chlamydia pneumoniae pneumonia in children hospitalized with community-acquired pneumonia at a single center in Korea in 2016. J Infect Chemother. 2023;29(5):453-7. 10.1016/j.jiac.2023.01.012 [DOI] [PubMed] [Google Scholar]
- 26. Tagini F, Opota O, Greub G. Chlamydia pneumoniae upsurge at tertiary hospital, Lausanne, Switzerland. Emerg Infect Dis. 2024;30(4):810-2. 10.3201/eid3004.231610 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R foundation for Statistical Computing; 2021. Available from: https://www.R-project.org
- 28.Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B.1995;57(1):289–300.
- 29. Voldstedlund M, Haarh M, Mølbak K, MiBa Board of Representatives . The Danish Microbiology Database (MiBa) 2010 to 2013. Euro Surveill. 2014;19(1):20667. 10.2807/1560-7917.ES2014.19.1.20667 [DOI] [PubMed] [Google Scholar]
- 30. Nordholm AC, Søborg B, Jokelainen P, Lauenborg Møller K, Flink Sørensen L, Grove Krause T, et al. Mycoplasma pneumoniae epidemic in Denmark, October to December, 2023. Euro Surveill. 2024;29(2):2300707. 10.2807/1560-7917.ES.2024.29.2.2300707 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Loens K, Beck T, Ursi D, Overdijk M, Sillekens P, Goossens H, et al. Evaluation of different nucleic acid amplification techniques for the detection of M. pneumoniae, C. pneumoniae and Legionella spp. in respiratory specimens from patients with community-acquired pneumonia. J Microbiol Methods. 2008;73(3):257-62. 10.1016/j.mimet.2008.02.010 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data are readily available in the manuscript or the Supplementary material.