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Atypical causes of respiratory virus infections in Sub-Saharan Africa from 2013– 2023: a systematic review and meta-analysis

BMC Infectious Diseases volume 25, Article number: 668 (2025) Cite this article

Abstract

Background

Atypical respiratory viruses (ARVs) are a diverse group of pathogens that cause respiratory infections through less common mechanisms or in unique epidemiological patterns, unlike the typical viruses like respiratory syncytial virus, influenza and human rhinoviruses. They sometimes present as unusual respiratory illnesses in vulnerable populations with near-fatal outcomes. Several viruses are involved, such as Human metapneumovirus (HMPV), Human Bocavirus (HBoV), Enteroviruses (EVs), Parechovirus (PeV) and Influenza C virus (ICV). This review was done to shed light on ARVs and their possible role in respiratory illness or infections based on studies in Sub-Saharan Africa from 2013 to 2023.

Methods

We systematically reviewed atypical causes of respiratory virus infections in Sub-Saharan Africa (SSA) in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines. We searched PubMed, Web of Science, Google Scholar and Cochrane Library to include studies published from 2013 to 2023 with reports on ARV. The protocol was registered in PROSPERO (ID: CRD42024611183).

Results

The review covered 46 SSA countries, with five eligible for the systematic review. The search yielded 548 publications, with only six studies meeting the inclusion criteria. Studies included children and individuals of all age groups. The prevalence of ARVs detected in SSA was as follows: HMPV pooled prevalence was 1.52% (95% CI: 1.07–2.00), EVs pooled prevalence was 15.0% (95% CI: 14.1–15.9), HBoV prevalence was 0.4%, PeV was 20%, and ICV was 1.3% in individuals with respiratory tract infection(s).

Conclusion

Our findings suggest testing or diagnostics for ARV infections are very low in SSA. Therefore, surveillance of people suffering from respiratory tract infections, which is lacking, needs to be improved to monitor the prevalence of ARVs and the role they play in respiratory disease outcomes.

Peer Review reports

Introduction

Respiratory viral infections are a major global health problem affecting all ages [1]. One of the major causes of morbidity and mortality in children worldwide is acute respiratory infections (ARI) [2]. Until recently, acute viral respiratory infections were not considered a major public health concern [3]. The first era in the discoveries of respiratory viruses occurred between 1933 and 1965, marked by the identification of several major respiratory viruses through virus culture techniques [4]. Influenza A virus was one of the first major respiratory viruses discovered in 1933, followed by coxsackie virus (1948), echovirus (1951), adenovirus (1953), respiratory syncytial virus (RSV) (1956), rhinovirus (1956), parainfluenza virus (1956), and coronavirus (CoV) (1965) [4]. These are often classified as typical respiratory viruses due to their well-documented role in respiratory infections. The 1990s saw major advancements in viral diagnostics with PCR, leading to the identification of additional pathogens. Events like the 1997 Hong Kong H5N1 outbreak, the 2003 SARS epidemic, and the 2009 H1N1 pandemic underscored the risks of respiratory viruses [5]. In contrast, atypical respiratory viruses (ARVs) cause infections through less common mechanisms or distinct epidemiological patterns. Also not often found implicated in respiratory infections in other parts of the world. For example, RSV is a leading cause of respiratory infections in children, with a detection rate of 27.9% in one study [6]. Defining ARVs alongside typical respiratory viruses is essential for understanding their epidemiology, clinical impact, and public health significance.

Viruses can infect both the upper and lower respiratory tract, termed Acute Respiratory Tract Infections (ARTI), which can be divided into upper respiratory tract infections (URIs) or lower respiratory tract infections (LRIs) [7]. Acute Respiratory Infections cause 12 million cases of morbidity and contribute to 1.3 million fatalities among children under the age of five globally each year. Three-quarters of these cases occur in Sub-Saharan Africa (SSA) [8]. The countries of sub-Saharan Africa have the second highest incidence of ARIs; together, they account for more than 80% of all cases worldwide [9]. The cause of most lower respiratory tract infections is associated with viral agents; however, even with advanced genomic amplification techniques, a viral agent is identified in only 40% of cases [10]. Research shows that some ARVs are responsible, at least in part, for illnesses that could not previously be linked to well-known respiratory viruses like RSV, rhinoviruses, influenza A virus, parainfluenza viruses, and adenoviruses [11]. These are based on their distinct epidemiological patterns and pathogenic mechanisms, which differentiate them from typical respiratory viruses [12]. These atypical viruses are often detected in specific populations like children and immunocompromised individuals and mostly present with milder symptoms like low-grade fever [13]. Also, ARVS are not often implicated in respiratory infections globally, but have been identified in specific cases or regions, underscoring the importance of ongoing surveillance and research [14]. Atypical respiratory viruses pose significant challenges in SSA. Most healthcare facilities in SSA lack the advanced diagnostic tools to identify respiratory viruses accurately; therefore, they cannot detect atypical viruses like Human Metapneumovirus (HMPV), Human Bocavirus (HBoV), Influenza C Virus (ICV), Enteroviruses (EVs), and Human Parechovirus (PeV).

Children and adults in SSA often face multiple infections simultaneously, such as HIV, tuberculosis, and malaria, which can complicate the diagnosis and treatment of respiratory infections [15]. Inadequate living conditions, poor nutrition, limited access to clean water, and poor sanitation are among the socioeconomic factors contributing to the high incidence of respiratory infections in Sub-Saharan Africa [16].This systematic review and meta-analysis present a focused summary of studies on atypical causes of respiratory virus infections in Sub-Saharan Africa, aiming to determine the contributions of specific respiratory viruses to the burden of acute respiratory infections. The main objective is to evaluate existing literature from 2013 to 2023 regarding prevalence, diagnostic methods, clinical significance, seasonality, and viral co-infections.

Methods

Settings

This systematic review focused on studies with ARVs from SSA countries. This review, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [17] Guidance focused on estimating the prevalence of atypical respiratory virus infections, identifying the diagnostic methods used for their detection, and evaluating their clinical significance.

Criteria for classification

In this review, we classified atypical respiratory viruses as respiratory infections that are under-reported and underrecognized or least recognized among the etiological agents of respiratory infections in sub-Saharan Africa [18, 19]. These viruses include HMPV [20], HBoV [21], ICV [22], EVs [23], and PeV [24, 25].

Protocol registration

The protocol for conducting this systematic review was registered in the International Prospective.

Register of Systematic Reviews (PROSPERO) (ID: CRD42024611183).

Searches

We conducted searches in electronic bibliographic databases and open-access journals, including PubMed, Web of Science, Google Scholar and Cochrane Library. Additionally, we reviewed the reference lists of included studies and relevant publications. The search strategy comprised terms related to key review concepts: Atypical respiratory viruses, Prevalence, and Sub-Saharan Africa. Each term was operationalized with various synonyms and tailored for specific databases. The search strategy used Medical Subject Heading (MeSH) terms and involved key terms with the appropriate Boolean operators (AND, OR) to ensure comprehensive coverage. No language restrictions were applied, and the searches were restricted to studies published between 2013 and 2023 for a ten-year coverage before the final analysis. This is to capture a wide range of literature on atypical respiratory viruses given a 10-year period and to maintain currency in the findings.

Study selection procedures

The inclusion and exclusion criteria were defined based on the Participants, Intervention/Exposure, Comparator, and Outcome (PICO) framework, as detailed below:

Participants/population

The review included analytical observational studies, longitudinal studies, and cross-sectional studies. Experimental study designs that report on prevalence were also considered. Individuals of all ages were considered independent of the administrative level (district, region, and nation). Infections caused by typical respiratory viruses, such as RSV, rhinoviruses, influenza A virus, parainfluenza viruses, and adenoviruses, were excluded.

Intervention(s)/exposure

The exposure of interest was the atypical respiratory virus infection. These viruses are HMPV, HBoV, ICV, EVs and PeV.

Comparator(s)/control

No comparator.

Main outcome

The main review outcome was atypical causes of respiratory viral infections, including clinical impact, manifestations and conditions associated with these viral infections in the population under investigation.

Additional outcome

Additional outcomes included the diagnostic methods used in detecting these viruses.

Eligibility criteria

  1. 1.

    Articles reported on atypical respiratory viruses as the exposure of interest.

  2. 2.

    Articles conducted in any of the Sub-Saharan African countries.

  3. 3.

    Studies published between the years 2013 and 2023.

  4. 4.

    Population-level, longitudinal or cross-sectional studies or facility-based (hospital) studies, independent of the administrative level (district, region, nation).

Study inclusion

Two independent reviewers, GA and OL, used the eligibility criteria to select studies for inclusion in the review. Any disagreement was resolved by discussion, and/or a third reviewer, PED, was consulted to reach a consensus.

Data extraction

We extracted the following data: author(s), publication year, study country, study period, prevalence of Atypical respiratory viruses, diagnostic methods, type of population (geographical region, cohort), and population baseline characteristics. Mendeley Desktop Version 1.19.8 was used to identify duplicate records.

Measures of effect

The review’s primary outcome was to assess the prevalence of ARV infections, as reported in primary studies. Secondary outcomes included diagnostic methods for detecting the clinical impact of these viruses.

Data analysis and synthesis

The reported prevalence for individual atypical viruses was summarised in tabular format. The diagnostic methods, co-infections and seasonality were identified and reported. A meta-analysis estimated the prevalence of identified atypical respiratory viruses in SSA with forest plot(s) and publication bias of included studies was assessed with funnel plot(s). Data analysis was conducted using StataSE 16 statistical software from StataCorp, College Station, Texas, USA.

Sensitivity analysis

Sensitivity analyses were carried out to investigate how non-eligible research may impact risk differences. This was accomplished by running the data through a meta-analysis twice. Only studies that were known to be eligible were included in the final meta-analysis.

Risk of bias (quality) assessment

Quality assessment of the studies included was performed by two independent reviewers based on the Newcastle-Ottawa Scale (NOS) score and any disparity were resolved by discussion and/or consulting a third reviewer (Appendix 1). In addition to the NOS score, we also considered the methodological rigor of each study, including factors such as study design, sample size, and data collection methods. This comprehensive assessment ensured a thorough evaluation of the quality of the included studies and provided confidence in the robustness of our findings.

Results

Study selection procedures

Figure 1 summarises the results of the study search and selection process. After removing duplicates, 543 studies were identified in the databases. During title and abstract screening, 454 were excluded, leaving 89 studies for full-text review. Six studies were included in the systematic review. The main reasons for exclusion from the review were reports outside the study area, studies unrelated to the objectives, and review papers.

Fig. 1
figure 1

Flow diagram of the study selection procedure

* records included

**records excluded

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Characteristics of included eligible studies

Table 1 summarises the characteristics of the six included studies. These studies were published between 2014 and 2022, with two papers published in 2014 and 2015, respectively. Two studies were conducted in Senegal. Among the eligible studies, three focused on children under five, two included participants of all ages and one targeted individuals over fifty years.

Table 1 Demographic characteristics of included studies
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Prevalence estimates

The prevalence of various atypical respiratory viruses across different African countries, as reported by included studies, are summarised in Table 2. HMPV prevalence ranges from 0.7% in Zambia [31] to 11.9% in Kenya [30]. HBoV prevalence was reported in Senegal [28], with a rate of 0.4%, while EVs show a wide range of prevalence, from 2.3 to 47.5%, as reported [28] and [30], respectively. PeVs were identified with a prevalence of 20% in Kenya [30] in 2015, whereas ICV was reported only in Côte D’Ivoire with a rate of 1.3% [29] in 2014.

Table 2 Prevalence of atypical respiratory viruses from included studies
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Diagnostic methods of detection used in the selected studies

The diagnostic methods employed across studies conducted in various African countries to detect ARV are outlined in Table 3. Multiplex PCR was utilised in Botswana [26] allowing simultaneous detection of multiple pathogens. Senegal-based studies used diverse techniques, including real-time PCR combined with cell culture [27] and a two-step real-time RT-PCR [28], which enhanced sensitivity and specificity. Côte D’Ivoire’s study, relied on conventional RT-PCR, a widely used method for detecting RNA viruses [29]. In Kenya, qRT-PCR was employed [30] for quantitative viral RNA detection. In Zambia [31], leveraged advanced diagnostic tools such as the FilmArray Respiratory Panel EZ and the ePlex Respiratory Pathogen Panel 2, integrating commercial multiplex Panels with automated systems for rapid pathogen detection.

Table 3 Methods employed by included studies
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Seasonality and clinical outcomes

Table 4 shows an overview of atypical respiratory viruses, detailing their seasonality, clinical outcomes, prevalence rates, and statistical significance. Human metapneumovirus (HMPV) is predominantly observed from December to March. It is associated with varying clinical presentations across studies, including acute lower respiratory infections (ALRI), influenza-like illness (ILI), and severe pneumonia. High prevalence rates ranged from 19 to 75.6%, with statistically significant p-values (< 0.001). Other viruses, such as HBoV, EVs, PeV, and ICV, demonstrate distinct seasonality patterns. HBoV is linked to July-August, while enteroviruses and parechoviruses are detected year-round. Clinical outcomes span fever, cough, sore throat, rhinitis, and severe respiratory symptoms like chest indrawing and oxygen desaturation.

Table 4a Seasonality and clinical outcome
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Table 4b Seasonality and clinical outcomes
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Atypical virus co-infection with other viruses

Table 5 shows data on co-infections between human rhinovirus (HRV) and enterovirus (EV) across studies, highlighting variations in prevalence and statistical significance. Botswana’s study reported a co-infection rate of 31% (n = 97) with no statistically significant association (p > 0.99) [26]. Senegal’s study observed a lower co-infection prevalence of 10.4% (n = 437) but found it statistically substantial (p < 0.05) [27] and Kenya’s study reported the highest HRV + EV co-infection prevalence at 47.5% (n = 97), though p-values were not provided [30]. Zambia’s study showed year-to-year variability, with co-infection rates of 17.9% in the first year and 19.4% in the second year, though statistical significance was not reported [31]. Notably, data on co-infection was unavailable in the studies by [28] and [29].

Table 5 Atypical virus co-infection with other viruses
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Pooled prevalence estimates

Figure 2. illustrates the diversity in prevalence among studies, with Kenya’s study reporting the highest prevalence [30], whereas Zambia’s (1st Year) study noted the lowest [31]. The aggregated estimate indicates an overall prevalence trend, representing the combined data from all included studies. This visual depiction emphasises variability and offers a comprehensive overview of HMPV prevalence, and the pooled prevalence across the included studies was 1.52% (95% CI: 1.07–2.00). There was a high heterogeneity as indicated by the I2 of 93.82% among the studies based on parameters (Cochrans’s Q statistic, Q = 64.69 and degrees of freedom, df = 4) used in the meta-analysis. And Fig. 3, is a forest plot showing the prevalence of Enterovirus from four individual studies and a pooled estimate. There was a variation in Enterovirus prevalence among the included studies, with some reporting much higher or lower prevalence than the pooled estimate which was 15.0% (95% CI: 14.1–15.9).

Fig. 2
figure 2

The pooled prevalence of Human Metapneumovirus (HMPV)). The forest plot depicts the prevalence of HMPV as reported by individual studies [26, 28, 30, 31] [1st Year and 2nd Year], with corresponding 95% confidence intervals (blue lines). The pooled prevalence, calculated using a random-effects model, is represented by the red diamond, with the red dashed line indicating the pooled estimate. The x-axis shows the prevalence (proportion), while the y-axis lists the studies included

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Fig. 3
figure 3

Pooled prevalence of Enterovirus. The forest plot illustrates the prevalence of Enterovirus reported by individual studies [26,27,28], and [30], with corresponding 95% confidence intervals (blue lines). The pooled prevalence, calculated using a random-effects model, is represented by the red diamond, while the red dashed line marks the pooled estimate. The x-axis displays the prevalence (proportion), and the y-axis lists the studies included in the analysis

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Statistical analysis for publication bias

We generated funnel plots for the detection of publication bias of the included papers. In this assessment, all studies included in the meta-analysis were at minimal risk of bias for HMPV (Fig. 4) and EV (Fig. 5).

Fig. 4
figure 4

Funnel plot assessing publication bias in a meta-analysis of HMPV prevalence. The x-axis represents the effect size, while the y-axis represents the standard error. Open circles indicate individual studies, and shaded areas represent confidence regions. The symmetrical distribution of studies around the central axis suggests minimal publication bias, with smaller studies (higher standard error) concentrated at the top and larger studies (lower standard error) spread at the base. The presence of studies across varying standard error levels supports the methodological robustness and validity of the meta-analysis findings

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Fig. 5
figure 5

Funnel plot assessing publication bias in a meta-analysis of Enterovirus (EV) prevalence. Open circles indicate individual studies, with different shapes and colors representing specific studies. The shaded regions denote confidence intervals, with darker shades indicating greater certainty. The symmetrical distribution of studies around the central axis suggests minimal publication bias, with smaller studies (higher standard error) clustered at the top and larger studies (lower standard error) spread at the base. The presence of studies across different standard error levels supports the methodological robustness and validity of the meta-analysis findings

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Discussion of key findings

This first systematic review focuses on atypical causes of respiratory virus infections in Sub-Saharan Africa (SSA). The results of this review are based on six studies conducted between 2014 and 2022, which detected and reported on five atypical viruses known to cause respiratory tract infections and pose a risk to young children, the elderly and immunocompromised individuals worldwide [7]. These five viruses are HMPV, HBoV, EVs, PeV, and ICV. The HMPV pooled estimate gave weight to studies with larger sample sizes, and the narrow confidence interval indicates a precise estimate. HMPV was the only virus detected more frequently in pneumonia cases among children 1 to 23 months than in control cases [15]. Wang et al.. discovered a slightly higher prevalence of HMPV in childhood (≤ 5 years) community-acquired pneumonia, 6.1% (95% CI: 4.1–8.1) in a recent meta-analysis comprising 21 studies [32]. The prevalence of HMPV in children and older adults in hospital inpatients or community studies varies greatly around the world, ranging from 1.7 to 17%. In general, the prevalence is higher in outpatients than inpatients and higher in children under five years than in older age groups [33]. HMPV follows a distinct seasonal pattern, peaking between December and March, particularly in temperate climates. This trend is linked to low temperatures, reduced humidity, indoor crowding, and seasonal immune suppression [34]. HMPV cases peak in winter-spring, especially in colder regions [35]. While RSV and Influenza A also show seasonal trends, HMPV remains underrecognized in surveillance. As an emerging cause of acute respiratory infections, particularly in children and immunocompromised individuals, understanding its seasonal patterns is essential for effective surveillance and prevention strategies.

A prevalence of 0.4% (1/270) was found for HBoV among adults with bone marrow transplants who had acute respiratory infections in São Paulo, Brazil, which may be due to their immuno-compromised state [36]. The number of studies on HBoV in adults suffering from respiratory tract infections is limited in SSA. However, a review of children less than 5 years from 11 African studies found a pooled prevalence for HBoV at 13% from children with gastroenteritis and respiratory tract infections [37].There is variation in Enterovirus prevalence across settings (Fig. 3). A 6.45% prevalence for EVs was reported in a developed country (Italy) for children with respiratory syndrome [38] which is a little higher than the 5% reported by Kelly et al.. in < 2-year-old children in a developing country. The slightly lower prevalence in the developing country could be due to underreporting, limited diagnostic capacity or differences in study methodologies. Parechovirus prevalence was 1.9% in < 5 years, as reported by Breiman et al.. Parechovirus infections normally affect neonates and young children less than 5 years of age, and clinical manifestations range from asymptomatic to life-threatening [39]. A surveillance study on Influenza C in Germany from 2012 to 2014 found the same prevalence, 1.3%, among pre-school children under 4 years old with respiratory infections. This was seen in data from the national influenza surveillance in Germany [40]. Preschool children have less mature immune systems than adults, making them more susceptible to respiratory infections, including Influenza C. They may lack prior exposure or immunity to this virus, which is critical for effective defense.

The diagnostic methods employed in the six studies were RT-PCR techniques. Due to the cost of purchase and operation for these techniques or equipment, most SSA hospitals or laboratories cannot afford to use them, leading to low or no detection of these atypical viruses among patients in these low-resource environments. There is a need for improved diagnostics and surveillance programs to target these viruses to reduce near-fatal condition(s) suffered by young children (< 5 years) and immunocompromised adult populations.

Only five of the 46 SSA countries (Botswana, Senegal, Côte d’Ivoire, Kenya, and Zambia) reported on atypical respiratory viruses. The findings highlight these viruses diverse epidemiological and clinical characteristics, emphasising their importance in public health. Therefore, it is essential to consider future longitudinal research design that explores seasonality on specific age-related vulnerabilities in these countries to determine the true burden of atypical respiratory viruses.

Furthermore, expanding on previous literature would provide a deeper context for these findings. Comparative studies from other global regions, particularly those with well-documented seasonal patterns and diagnostic advancements, could enhance understanding of the epidemiology, transmission dynamics, and clinical impact of these atypical respiratory viruses in Sub-Saharan Africa [41]. Studies from North America and Europe indicate that HMPV infections are frequently underreported, with detection rates significantly improving with enhanced diagnostic methods such as next-generation sequencing [42]. Additionally, discussing the clinical implications of ARVs in detail, including their impact on healthcare systems, treatment strategies, and public health interventions, would strengthen the discussion [43]. For instance, targeted vaccination strategies have been proposed for high-risk populations in developed countries, an approach that could be adapted to SSA settings with improved epidemiological data [44]. Highlighting potential policy recommendations for improving diagnostic access and surveillance in SSA would also be beneficial, particularly in integrating viral surveillance with existing disease monitoring programs for influenza and respiratory syncytial virus [45]. The strength of this review was systematically synthesizing scarce evidence on atypical respiratory viruses in SSA, combining meta-analysis for robust conclusions whilst the limitations was methodological heterogeneity due to variations in diagnostic tools and surveillance across different countries, alongside limited data availability from certain regions potentially introducing bias. However, in terms of the above issues, it remains highly relevant to public health and infectious disease research, offering novel perspectives on an often-overlooked issue.

Conclusion

More studies are required in SSA, both urban and rural settings, to monitor the prevalence of respiratory viruses, including ARVs. This will help understand the role of ARVs in individuals found in this review, especially children and adult populations with susceptibility to acute or chronic respiratory tract infection and their clinical significance. ARV infections are underreported in SSA, considering the cost of testing and laboratory set-up. Variations in diagnostic methods highlight technological diversity and evolving approaches across regions. There is need for further investigation into HRV and EV co-infections in different settings. This review shed light on ARVs, their possible role in respiratory illness, and likely important pathogens to consider when developing technologies and packaging strategies to prevent severe acute respiratory infection.

Data availability

All data generated or analysed during this study are included in this published article and captured in supplementary information file 4.

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Acknowledgements

Thank you to the management of the German-West African Centre for Global Health and Pandemic Prevention (G-WAC) / Berlin University Alliance (BUA) for their financial and technical support.

Funding

The work was made possible by the German-West African Centre for Global Health and Pandemic Prevention (G-WAC) scholarship of the German Academic Exchange Service (DAAD) as part of the Global Centres Programme funded by the German Federal Foreign Office. The Flattening the Curve Project of the Berlin University Alliance (BUA) provided additional financial support for supervision.

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Authors and Affiliations

  1. Department of Clinical Microbiology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    George Agyei, Brice Armel Nembot Fogang, Sherihane Aryeetey & Yaw Adu-Sarkodie

  2. German West-African Centre for Global Health and Pandemic Prevention, Kumasi, Ghana

    George Agyei, Philip El-Duah, Jonathan Mawutor Gmanyami, Brice Armel Nembot Fogang, Sherihane Aryeetey & Michael Owusu

  3. One Health Virology Research Group, Kumasi Centre for Collaborative Research in Tropical Medicine, Kumasi, Ghana

    George Agyei, Sherihane Aryeetey, Augustina Sylverken & Michael Owusu

  4. Department of Medical Diagnostics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Michael Owusu

  5. Institute of Virology, Charité-Universitätsmedizin Berlin, Berlin, Germany

    Philip El-Duah, Rexford Mawunyo Dumevi & Christian Drosten

  6. Global Health and Infectious Diseases Research Group, Kumasi Centre for Collaborative Research in Tropical Medicine, Kumasi, Ghana

    Jonathan Mawutor Gmanyami

  7. School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Jonathan Mawutor Gmanyami & Oscar Lambert

  8. Department of Theoretical and Applied Biology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Augustina Sylverken

  9. Kumasi Centre for Collaborative Research in Tropical Medicine (KCCR), Kumasi, Ghana

    Richard Odame Phillips

  10. School of Medicine and Dentistry, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Richard Odame Phillips

  11. German Centre for Infection Research, Berlin, Germany

    Christian Drosten

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  1. George Agyei
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Contributions

GA, MO, PED, AS, RMD, YAS, ROP, CD, JMG, BANF and SA made substantial contributions to the conception, design and write-up of this systematic review. GA performed the screening, study selection and data extraction from all studies using the eligibility criteria. OL independently screened the titles and abstracts of the identified studies. All authors approved the final version of this manuscript.

Corresponding author

Correspondence to Michael Owusu.

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Agyei, G., El-Duah, P., Gmanyami, J.M. et al. Atypical causes of respiratory virus infections in Sub-Saharan Africa from 2013– 2023: a systematic review and meta-analysis. BMC Infect Dis 25, 668 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12879-025-11028-9

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BMC Infectious Diseases

ISSN: 1471-2334

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