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Background: Rift Valley Fever (RVF) is a mosquito-borne zoonotic disease that poses a serious threat to both humans and livestock across various regions, particularly in Africa, the Arabian Peninsula, and parts of the Indian Ocean Islands. This study seeks to analyze the spatial and temporal distribution and trends of RVF outbreaks within the East African Community (EAC) countries, offering insights into the patterns and progression of these outbreaks in the region., Methods: We conducted a retrospective analysis of the Program for Monitoring Emerging Diseases (ProMed), a digital, event-based disease surveillance system, to identify reports of outbreak events in Uganda, Kenya, Rwanda, Burundi, Tanzania, and South Sudan from 2010 to 2024. Outbreak events were systematically tabulated by year, and each record was reviewed to assess RVF outbreak characteristics, locations, trends, and spatial-temporal distribution over the past 14 years., Results: Between 2010 and 2024, 67 RVF outbreaks were documented across Uganda, Rwanda, Kenya, Tanzania, Burundi, and South Sudan, impacting both animal and human populations with confirmed cases and fatalities. Key interventions to contain these outbreaks included restricting animal movement, vaccination campaigns, disease awareness initiatives, enhanced surveillance, contact tracing, isolation, and treatment. Reporting of these outbreaks varied across regions, with a notable monthly increase in cases during May and June and the highest annual incidence observed in 2018., Conclusion: The recurrent and widespread outbreaks of Rift Valley Fever across East Africa highlight an urgent need for increased investment in research, surveillance, prevention, and control efforts to combat this disease., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ndishimye, Umuhoza, Umutoni, Zakham, Ndayambaje, Hewins, Ngabo Gasana, Ostadgavahi, Sganzerla, Ndayisenga, Kelvin and Udahemuka.)

Background: Human Respiratory Syncytial Virus (HRSV), Human Parainfluenza Virus (HPIV), and Human Adenovirus (HAdV) epidemics differ in geographical location, time, and virus type. Regions prone to infections can be identified using geographic information systems (GIS) and available methods for detecting spatial and time clusters. We sought to find statistically significant spatial and time clusters of HRSV, HPIV, and HAdV cases in different parts of Kenya., Methods: To analyse retrospective data, we used a geographical information system (GIS) and the spatial scan statistic. The information was gathered from surveillance sites and aggregated at the county level in order to identify purely spatial and Spatio-temporal clusters. To detect the presence of spatial autocorrelation, the local Moran's I test was used. To detect the spatial clusters of HRSV, HPIV, and HAdV cases, we performed the purely spatial scan statistic. Furthermore, space-time clusters were identified using space-time scan statistics. Both spatial and space-time analyses were based on the discrete Poisson model with a pre-specified statistical significance levelof p<0.05., Results: The findings showed that HRSV, HPIV, and HAdV cases had significant autocorrelation within the study areas. Furthermore, in the Western region of the country, the three respiratory viruses had local clusters with significant positive autocorrelation (p<0.05). Statistically, the Western region had significant spatial clusters of HRSV, HPIV, and HAdV occurrence. Furthermore, the space-time analysis revealed that the HPIV primary cluster persisted in the Western region from 2007 to 2013. However, primary clusters of HRSV and HAdV were observed in the Coastal region in 2009-11 and 2008-09, respectively., Conclusion: Human respiratory syncytial virus (HRSV), human parainfluenza virus (HPIV), and human adenovirus (HAdV) hotspots (clusters) occurred in Kenya's Western and Coastal regions from 2007 to 2013. The Western region appeared to be more prone to the occurrence of allthree respiratory viruses throughout the study period. Strategic mitigation should focus on these locations to prevent future clusters of HRSV, HPIV, and HAdV infections that could lead to epidemics., (© The East African Health Research Commission 2022.)

Background: Human respiratory syncytial viruses (HRSV), human parainfluenza viruses (HPIV), and human adenoviruses (HAdVs) cause a substantial morbidity burden globally., Objective: We sought to estimate morbidity burden, assess seasonality, and determine factors associated with these respiratory viruses in Kenya., Methods: The data were obtained from Kenyan sites included in the Köppen-Geiger climate classification system. We defined the proportion of morbidity burden by descriptive analysis and visualized time-series data for January 2007-December 2013. Logistic regression was used to identify factors associated with infection outcomes., Results: The morbidity burden for HRSV was 3.1%, HPIV 5.3% and HAdVs 3.3%. Infants were more likely to be infected than other age groups. HRSV exhibited seasonality with high occurrence in January-March (odds ratio[OR] = 2.73) and April-June (OR = 3.01). Hot land surface temperature (≥40 °C) was associated with HRSV infections (OR = 2.75), as was warmer air temperature (19-22.9 °C) (OR = 1.68), compared with land surface temperature (<30) and cooler air temperature (<19 °C) respectively. Moderate rainfall (150-200 mm) areas had greater odds of HRSV infection (OR = 1.32) than low rainfall (<150 mm)., Conclusion: HRSV, HPIV and HAdVs contributed to morbidity burden, and infants were significantly affected. HRSV had a clear seasonal pattern and were associated with climate parameters, unlike HPIV and HAdVs., Competing Interests: The authors declare that they have no financial or personal relationships which may have an inappropriate influence on conducting this study., (© 2021 The Author(s).)

Background: Viruses are responsible for a large proportion of acute respiratory tract infections (ARTIs). Human influenza, parainfluenza, respiratory-syncytial-virus, and adenoviruses are among the leading cause of ARTIs. Epidemiological evidence of those respiratory viruses is limited in the East Africa Community (EAC) region. This review sought to identify the prevalence of respiratory syncytial virus, parainfluenza, and adenoviruses among cases of ARTI in the EAC from 2007 to 2020., Methods: A literature search was conducted in Medline, Global Index Medicus, and the grey literature from public health institutions and programs in the EAC. Two independent reviewers performed data extraction. We used a random effects model to pool the prevalence estimate across studies. We assessed heterogeneity with the I2 statistic, and Cochran's Q test, and further we did subgroup analysis. This review was registered with PROSPERO under registration number CRD42018110186., Results: A total of 12 studies met the eligibility criteria for the studies documented from 2007 to 2020. The overall pooled prevalence of adenoviruses was 13% (95% confidence interval [CI]: 6-21, N = 28829), respiratory syncytial virus 11% (95% CI: 7-15, N = 22627), and parainfluenza was 9% (95% CI: 7-11, N = 28363). Pooled prevalence of reported ARTIs, all ages, and locality varied in the included studies. Studies among participants with severe acute respiratory disease had a higher pooled prevalence of all the three viruses. Considerable heterogeneity was noted overall and in subgroup analysis., Conclusion: Our findings indicate that human adenoviruses, respiratory syncytial virus and parainfluenza virus are prevalent in Kenya, Tanzania, and Uganda. These three respiratory viruses contribute substantially to ARTIs in the EAC, particularly among those with severe disease and those aged five and above., Competing Interests: The authors have declared that no competing interests exist.

Background: Influenza viruses remain a global threat with the potential to trigger outbreaks and pandemics. Globally, seasonal influenza viruses' mortality range from 291 243-645 832 annually, of which 17% occurs in Sub-Saharan Africa. We sought to estimate the overall prevalence of influenza infections in Kenya, identifying factors influencing the distribution of these infections, and describe trends in occurrence from 2007 to 2013., Methods: Surveillance was conducted at eight district hospital sites countrywide. Participants who met the case definition for influenza-like illness were enrolled in the surveillance program. The nasopharyngeal specimens were collected from all participants. We tested all specimens for influenza viruses with quantitative reverse transcriptase real-time polymerase chain reaction (RT-qPCR) assay. Bivariate and multivariate log-binomial regression was performed with a statistically significant level of p<0.005. An administrative map of Kenya was used to locate the geographical distribution of surveillance sites in counties. We visualized the monthly trend of influenza viruses with a graph and chart using exponential smoothing at a damping factor of 0.5 over the study period (2007-2013)., Results: A total of 17446 participants enrolled in the program. The overall prevalence of influenza viruses was 19% (n = 3230), of which 76% (n = 2449) were type A, 21% (n = 669) type B and 3% (n = 112) A/ B coinfection. Of those with type A, 59% (n = 1451) were not subtyped. Seasonal influenza A/H3N2 was found in 48% (n = 475), influenza A/H1N1/pdm 2009 in 43% (n = 434), and seasonal influenza A/ H1N1 in 9% (n = 88) participants. Both genders were represented, whereas a large proportion of participants 55% were ≤1year age. Influenza prevalence was high, 2 times more in other age categories compared to ≤1year age. Category of occupation other than children and school attendees had a high prevalence of influenza virus (p< <0.001). The monthly trends of influenza viruses' positivity showed no seasonal pattern. Influenza types A and B co-circulated throughout the annual calendar during seven years of the surveillance., Conclusions: Influenza viruses circulate year-round and occur among children as well as the adult population in Kenya. Occupational and school-based settings showed a higher prevalence of influenza viruses. There were no regular seasonal patterns for influenza viruses., Competing Interests: The authors have declared that no competing interests exist.

Rift Valley fever (RVF) virus is caused by a zoonotic arbovirus that is endemic to eastern and southern Africa. It has also been reported in West and North Africa, Madagascar and the Arabian Peninsula. The virus is transmitted by mosquitoes, but people can also become infected while handling blood or other body fluids of animals and humans with RVF. In 2007, there was a large outbreak of RVF in Kenya, Tanzania, Sudan and Somalia. Outbreaks were also reported in South Africa in 2008-2011. The epidemiology of RVF and factors for disease occurrence in Rwanda are neither clear nor documented. Therefore, we conducted a crosssectional study from December 2012 to March 2013 to generate baseline information on RVF in cattle. Purposive sampling of cattle (n = 595) was done in six districts, and serum samples were screened with competitive enzyme-linked immunosorbent assay (ELISA). We performed a statistical analysis on the generated data, and risk factors associated with RVF seroprevalence were determined by a simple logistic regression. Overall, RVF seroprevalence was 16.8% (95% confidence interval [CI] [13.8% - 20.0%]). The highest seroprevalence was recorded in Kirehe district (36.9%) followed by Ngoma (22.3%), and the least was recorded in Nyagatare (7.9%). RVF was more likely to occur in adult cattle (19.9% [odds ratio {OR} = 1.88, 95% CI {0.98-3.61}]) compared to young cattle (10.5% [OR = 0.47, 95% CI {0.26-0.83}]). Pure exotic or cross-breeds were significantly exposed to RVF virus (seroprevalence 22.9% [OR = 4.26, 95% CI {1.82-9.99}]) in comparison to 14.1% (OR = 0.55, 95% CI [0.35-0.86]) in local breeds. Sex differences were not statistically significant. These findings indicated that cattle have been exposed to RVF virus in six districts in Rwanda with a significant risk in adult, exotic or cross-breeds in Kirehe district.