Makela, H. | Search bioRxiv

bioRxiv2026

Rat hepatitis E virus and novel paramyxoviruses in synanthropic rodents and shrews in Kenya

The majority of emerging infectious diseases are zoonotic, having their origin in wildlife before spilling over into the human population. While small mammals are recognized as critical reservoirs for these viruses, their viral diversity remains largely uncharacterized across many African countries. We conducted molecular surveillance of synanthropic rodents and shrews in the Kibera informal settlement in Nairobi and the rural Taita Hills region of Kenya to detect and characterize potential zoonotic viruses. Tissue samples from 228 rodents and shrews were screened for six viral families using PCR assays. Rat hepatitis E virus (HEV) (Rocahepevirus ratti), a rodent-associated virus with potential for human spillover, was identified in Mus musculus and Rattus norvegicus from Kibera. NGS was conducted for the HEV positive samples, and we obtained two near-complete HEV genomes from Rattus norvegicus, which clustered within rodent-associated HEV genotypes in the phylogenetic analysis. The two sequences from the Rattus norvegicus cluster together, indicating a close genetic relationship. Paramyxoviruses belonging to the genera Jeilongvirus and Parahenipavirus were detected both from Taita and Kibera in nine different samples from Rattus norvegicus, Mus minutoides, Crocidura sp and Acomys ignitus. One paramyxovirus positive sample (Acomys ignitus) from Taita was selected for further sequencing with NGS, and a complete genome of a new jeilongvirus was assembled. Phylogenetic analysis of the detected viruses confirmed the close relation to previously known rodent-borne jeilongviruses but also revealed potentially novel jeilong- and parahenipavirus species. Our findings highlight the circulation of potentially zoonotic viruses in both urban and rural small mammals in Kenya. It emphasizes the necessity of continued genomic surveillance of zoonotic viruses to mitigate risks of their spillover into human populations. HighlightsO_LISurveillance reveals diverse rodent-borne viruses circulating in Kenya. C_LIO_LIRat-HEV was detected in Rattus norvegicus and Mus musculus from an urban low-income area. C_LIO_LIParamyxoviruses were detected across multiple rodent and shrew species, including novel Acomys ignitus jeilongvirus. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/719784v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@86c94aorg.highwire.dtl.DTLVardef@10946adorg.highwire.dtl.DTLVardef@1ff45eforg.highwire.dtl.DTLVardef@4876f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Modeling the spatio-temporal annual changes in human tick-borne encephalitis (TBE) risk in Europe

IntroductionTick-borne encephalitis (TBE), caused by tick-borne encephalitis virus (TBEV), is a zoonotic disease that can cause severe neurological symptoms. Given the increasing number of reported human TBE cases in Europe, a spatio-temporal predictive model to infer the year-to-year probability of human TBE occurrence across Europe at the regional and municipal administrative levels was developed. MethodsThe distribution of human TBE cases at the regional (NUTS-3) level during the period 2017-2022, was derived by using data provided by the European surveillance system (TESSy, ECDC), and at the municipal level by using data from Austria, Finland, Italy, Lithuania, and Slovakia. The probability of presence of human TBE cases at the regional and municipal levels for the period 2017-2024 was modeled with a boosted regression trees model, including covariates that affect both the natural hazard of virus circulation and human exposure to tick bites. ResultsAreas with the highest probability of human TBE infections are primarily located in central-eastern Europe, the Baltic states, and along the coastline of Nordic countries up to the Bothnian Bay. Our results also highlight a statistically significant rising trend in the probability of human TBE infections not only in north-western, but also in south-western European countries, offering a spatio-temporal predictive framework for the assessment of areas where human TBE infection are most likely to occur. The model showed good predictive performance, with a mean AUC of 0.85 (SD = 0.02), sensitivity of 0.82, and specificity of 0.80 at the regional level, and a mean AUC of 0.82 (SD = 0.03), sensitivity of 0.80, and specificity of 0.69 at the municipal level. DiscussionWith ongoing climate and land use changes, the number of human TBE cases is likely to increase and expand into new areas, as trends are already indicating. This underscores the need for predictive models that can help prioritize intervention efforts. The approach adopted, by leveraging lagged covaries, enables timely one-year-ahead predictions, thus supporting surveillance, prevention, and control of human TBE infections by public health authorities. StatementsO_ST_ABSEthical statementC_ST_ABSEthical approval was not needed. Funding statementThis project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 874850 and is catalogued as MOOD 081. The contents of this publication are the sole responsibility of the authors and dont necessarily reflect the views of the European Commission. Conflict of interestNone. Authors contributionsFrancesca Dagostin: Conceptualization, Methodology, Data Curation, Formal Analysis, Writing - Original Draft. Diana Erazo: Conceptualization, Methodology, Writing - Review & Editing. Giovanni Marini: Conceptualization, Methodology, Writing - Review & Editing. Daniele Da Re: Conceptualization, Methodology, Writing - Review & Editing. Valentina Tagliapietra: Conceptualization, Methodology, Writing - Review & Editing. Maria Avdicova: Resources, Writing - Review & Editing. Tatjana Av[s]i[c] - [Z]upanc: Resources, Writing - Review & Editing. Timothee Dub: Conceptualization, Resources, Writing - Review & Editing. Nahuel Fiorito: Resources, Writing - Review & Editing. Nata[s]a Knap: Resources, Writing - Review & Editing. Celine M. Gossner: Resources, Writing - Review & Editing. Jana Kerlik: Resources, Writing - Review & Editing. Henna Makela: Resources, Writing - Review & Editing. Mateusz Markowicz: Resources,Writing - Review & Editing. Roya Olyazadeh: Resources, Writing - Review & Editing. Lukas Richter: Resources, Writing - Review & Editing. William Wint: Resources, Writing - Review & Editing. Maria Grazia Zuccali: Resources, Writing - Review & Editing. Milda [Z]ygutiene: Resources, Writing - Review & Editing. Simon Dellicour: Methodology, Writing - Review & Editing. Annapaola Rizzoli: Conceptualization, Methodology, Writing - Review & Editing. Data availabilityThe data that support the findings of this study were provided by ECDC, Azienda Provinciale per i Servizi Sanitari Provincia Autonoma di Trento (APSS), Unita Locale Socio Sanitaria Dolomiti (ULSS N.1 Dolomiti), Public Health Authority of the Slovak Republic, Austrian Agency for Health and Food Safety (AGES), Finnish Institute for Health and Welfare (THL), National Public Health Center under the Ministry of Health (Lithuania) and University of Ljubljana. Restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. The interactive risk maps can be explored in detail at https://mood-platform.avia-gis.com. DisclaimerThe views and opinions of the authors expressed herein do not necessarily state or reflect those of ECDC. The accuracy of the authors statistical analysis and the findings they report are not the responsibility of ECDC. ECDC is not responsible for conclusions or opinions drawn from the data provided. ECDC is not responsible for the correctness of the data and for data management, data merging and data collation after provision of the data. ECDC shall not be held liable for improper or incorrect use of the data.

ecology↗