Our study highlights the epidemic spread of M. pneumoniae during the winter season 2015 and spring / summer 2018 in Germany. M. pneumoniae re-emergence in 2023/2024 in Germany is comparable to the pre-pandemic number of cases. Cases in the second quartile 2024 were decreasing. In contrast to other bacterial pathogens e.g. Streptococcus pyogenes ([9]), which caused massive outbreaks after the Covid-19 pandemic, current spread of M. pneumoniae has not exceeded the historical number of cases even though testing capacity has dramatically increased over time. Interestingly, most M. pneumoniae patients were young and not hospitalized. Still, hospitalized M. pneumoniae patients were significantly older. This contrasts current data from the Netherlands and Denmark [6, 7] who frequently observed hospitalization and 11% had severe M. pneumoniae CAP which needed treatment in the intensive-care unit. We noticed fluctuating incidences of M. pneumoniae since 2015 corresponding to reported epidemics with M. pneumoniae.
Current empirical treatment of CAP with beta-lactam with or without beta-lactamase-inhibitor is not active for M. pneumoniae. Treatment options include tetracycline, quinolones and macrolides. Addition of a macrolide to empirical treatment of CAP is currently limited by guidelines to severely ill hospitalized patients with CAP. Current treatment algorithms will withhold active antibiotic treatment in most cases as shown by our data as patients were mainly observed in the outpatient setting. Unfortunately, proportions of macrolide-resistant M. pneumoniae are constantly rising and have increased worldwide from 18.2% in 2000 to 76.5% in 2019 [10]. Macrolide resistance is less pronounced in Europe with 5% resistant isolates. On the basis of this data we advise for the implementation of the following interventions a) introduction of a reporting obligation in Germany to early detect epidemics b) adjustment of empirical antimicrobial treatment for in- and outpatients during epidemics of M. pneumoniae and c) the limitation of macrolide use in CAP and other diseases (e.g. sexually transmitted diseases) to microbiologically confirmed or severe cases outside epidemics to avoid evolution of antimicrobial resistance in Germany.
Our data is in line with previously reported epidemics of M. pneumoniae occurring every 3–7 years. The most plausible explanation is that in contrast to many other bacterial infections the adaptive immune system plays a central role for protections. Low Mycoplasma-specific IgG antibodies that are induced during symptomatic infection but not in asymptomatic carriers increase the risk for infection [11, 12]. In contrast, pre-existing high titers of IgG have been shown to be protective of M. pneumoniae infection in non-smokers [11], but titers of IgG decline over time. During the COVID-19 pandemic low numbers of M. pneumoniae cases have been reported [8, 13]. Non-pharmaceutical interventions (NPI) have been shown to be protective of SARS-Cov-2 infection and infection with other respiratory viruses [14] and have also been also protective for M. pneumoniae [13]. Since infections with M. pneumoniae are distributed by droplets like other respiratory viruses and SARS-Cov-2 NPI must have had an effect on M. pneumoniae distribution in the population during COVID-19 pandemic. This might have led to declining antibody titers in the population, increased susceptibility and current M. pneumoniae epidemic in Germany [8].
Furthermore, co-infection was observed in every fifth patient with influenza A/B and rhinovirus being most prevalent. This is in line with a large-scale outbreak in France in 2024. This cohort is characterized by a high number of pediatric outpatients which confirms clinical data on M. pneumoniae CAP to be less severe. Adult patients were the minority of M. pneumoniae cases in most seasons in our cohort. This contrasts recent data from Denmark where 7% of children, 19% of adult patients aged 19–74 years and 48% >75 years were hospitalized over several seasons [6]. M. pneumoniae was reported to be among the five most common pathogens of severe CAP [4]. Current German guidelines on CAP advise against routine testing for M. pneumoniae in adults and children. Therefore, the following hypothesis can be raised which should be targeted by future studies: I) Pediatricians are more aware of M. pneumoniae CAP. II) Adult CAP patients are highly underdiagnosed with M. pneumoniae in Germany.
Our study has some limitations: No information on clinical disease and course of infections was available. Long-term colonization and asymptomatic carriers with M. pneumoniae have been reported, but should then also have been detected during the Covid-19 pandemic. Also, higher bacterial load has been reported in symptomatic patients. We cannot measure the rate of secondary hospitalizations of patients which might have led to an overestimation of outpatients in our cohort. Furthermore, we cannot estimate incidence of M. pneumoniae in all areas of Germany since most patients were localized in the North and/or West of Germany (supplementary Fig. 1). An epidemic situation of M. pneumoniae infections has been reported by adjacent countries in 2023/2024 which suggests generalizability of our results [6, 7]. Detection of pathogens tested outside of the panels described was not included into the analysis. Therefore, the rate of coinfection could be higher, especially during COVID-19 pandemic.
In conclusion, empirical treatment of CAP patients often does not include coverage of M. pneumoniae. Based on a more thorough implementation of available surveillance data into clinical routine, respective therapies could be adapted more quickly during epidemic outbreaks of M. pneumoniae infections. As hospitalization is increased in adult patients and severe courses of disease have been frequently reported, physicians should be aware and test for M. pneumoniae in CAP.
Table 1
Baseline characteristics of Mycoplasma pneumoniae positive patients
Baseline characteristics | Total | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
Total | 1448 | 23 | 23 | 44 | 26 | 85 | 61 | 0 | 9 | 485 | 692 |
age (median, interquartile range) | 11 (8–17) | 7.5 (6–26) | 24 (11–42) | 9 (8-19.5) | 14.5 (8.3–43.0) | 10.0 (6–14) | 10.0 (8–21.0) | na | 32.0 (11–39) | 10.5 (7–15) | 11 (8–17) |
age groups years (%) − 0–18 − 19–59 - >59 | 1090 (75.7) | 15 (68.2) | 9 (42.9) | 30 (69.7) | 16 (66.7) | 67 (78.8) | 44 (74.6) | na | 4 (44.4) | 387 (80.2) | 518 (75.0) |
307 (21.3) | 6 (27.3) | 9 (42.9) | 10 (23.3) | 5 (20.8) | 15 (17.6) | 14 (23.7) | na | 4 (44.4) | 87 (18.0) | 157 (22.8) |
42 (2.3) | 1 (4.5) | 3 (14.2) | 3 (7.0) | 3 (12.5) | 3 (3.5) | 1 (1.6) | na | 1 (11.1) | 8 (1.7) | 15 (2.2) |
sex (% females) | 690 (47.7) | 15 (66.2) | 5 (21.7) | 19 (43.8) | 16 (61.5) | 45 (52.9) | 24 (39.3) | na | 6 (66.7) | 244 (50.3) | 317 (45.8) |
outpatients (%) | 1375 (95.0) | 22 (95.6) | 18 (78.3) | 40 (90.9) | 22 (84.6) | 74 (87.1) | 55 (90.2) | na | 8 (88.9) | 469 (96.7) | 667 (96.4) |