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Mosquito-borne viral diseases such as dengue fever, chikungunya, and yellow fever have been documented in Ethiopia since the 1960s. However, the efficacy of public health insecticides against Aedes aegypti that transmits these viruses remains poorly understood in the country, particularly in the Afar Region. Thus, the aim of the study was to assess the susceptibility status of Ae. aegypti to deltamethrin, permethrin, alpha-cypermethrin, pirimiphos-methyl, bendiocarb, and propoxur insecticides. Larvae and pupae of Aedes species were collected from Awash Arba, Awash Sebat, and Werer towns of the Afar Region of Ethiopia during July-October 2022, brought to the Aklilu Lemma Institute of Pathobiology, insectary and reared to adults. Non-blood-fed, 3-5 days-old females Ae. aegypti were exposed to pyrethroid, carbamate, and organophosphate insecticide impregnated papers in tube test following the standard guidelines. Knockdown rates were noted at 10 minutes interval until one hour. The mortality in mosquitoes was recorded 24 hours after 60 minutes of exposure. The mortality rates of Ae. aegypti exposed to propoxur were 87% in all the study towns. Similarly, 88% mortality in Ae. aegypti was recorded when tested with bendiocarb in Awash Sebat and Awash Arba towns. Suspected resistance of Ae. aegypti (95% mortality) to alpha-cypermethrin was observed in Awash Arba town. However, Ae. aegypti collected from all the three sites was observed to be susceptible to deltamethrin, permethrin, and pirimiphos-methyl. Ae. aegypti was resistant to 0.1% bendiocarb and 0.1% propoxur and possibly resistant to 0.05% alpha-cypermethrin. On the other hand, it was susceptible to 0.05% deltamethrin, 0.75% permethrin, and 0.25% pirimiphos-methyl. Thus, vector control products with deltamethrin, permethrin, and pirimiphos-methyl can be used in the control of adult Ae. aegypti in the Afar Region of Ethiopia. However, further studies should be carried out to evaluate the susceptibility status of Ae. aegypti to alpha-cypermethrin in the Awash Arba area.

Neglected tropical diseases (NTDs) primarily affect the poorest populations, often living in remote, rural areas, urban slums or conflict zones. Arboviruses are a significant NTD category spread by mosquitoes. Dengue, Chikungunya, and Zika are three arboviruses that affect a large proportion of the population in Latin and South America. The clinical diagnosis of these arboviral diseases is a difficult task due to the concurrent circulation of several arboviruses which present similar symptoms, inaccurate serologic tests resulting from cross-reaction and co-infection with other arboviruses. The goal of this paper is to present evidence on the state of the art of studies investigating the automatic classification of arboviral diseases to support clinical diagnosis based on Machine Learning (ML) and Deep Learning (DL) models. We carried out a Systematic Literature Review (SLR) in which Google Scholar was searched to identify key papers on the topic. From an initial 963 records (956 from string-based search and seven from a single backward snowballing procedure), only 15 relevant papers were identified. Results show that current research is focused on the binary classification of Dengue, primarily using tree-based ML algorithms. Only one paper was identified using DL. Five papers presented solutions for multi-class problems, covering Dengue (and its variants) and Chikungunya. No papers were identified that investigated models to differentiate between Dengue, Chikungunya, and Zika. The use of an efficient clinical decision support system for arboviral diseases can improve the quality of the entire clinical process, thus increasing the accuracy of the diagnosis and the associated treatment. It should help physicians in their decision-making process and, consequently, improve the use of resources and the patient's quality of life.

Arboviruses infecting people primarily exist in urban transmission cycles involving urban mosquitoes in densely populated tropical regions. For dengue, chikungunya, Zika and yellow fever viruses, sylvatic (forest) transmission cycles also exist in some regions and involve non-human primates and forest-dwelling mosquitoes. Here we review the investigation methods and available data on sylvatic cycles involving non-human primates and dengue, chikungunya, Zika and yellow fever viruses in Africa, dengue viruses in Asia and yellow fever virus in the Americas. We also present current putative data that Mayaro, o’nyong’nyong, Oropouche, Spondweni and Lumbo viruses exist in sylvatic cycles.

Over the past decades, the number of arthropod-borne virus (arbovirus) outbreaks has increased worldwide. Knowledge regarding the sylvatic cycle (i.e., non-human hosts/environment) of arboviruses is limited, particularly in Africa, and the main hosts for virus maintenance are unknown. Previous studies have shown the presence of antibodies against certain arboviruses (i.e., chikungunya-, dengue-, and Zika virus) in African non-human primates and bats. We hypothesize that small mammals, specifically rodents, may function as amplifying hosts in anthropogenic environments. The detection of RNA of most arboviruses is complicated by the viruses’ short viremic period within their hosts. An alternative to determine arbovirus hosts is by detecting antibodies, which can persist several months. Therefore, we developed a high-throughput multiplex immunoassay to detect antibodies against 15 medically relevant arboviruses. We used this assay to assess approximately 1,300 blood samples of the multimammate mouse, Mastomys natalensis from Tanzania. In 24% of the samples, we detected antibodies against at least one of the tested arboviruses, with high seroprevalences of antibodies reacting against dengue virus serotype one (7.6%) and two (8.4%), and chikungunya virus (6%). Seroprevalence was higher in females and increased with age, which could be explained by inherent immunity and behavioral differences between sexes, and the increased chance of exposure to an arbovirus with age. We evaluated whether antibodies against multiple arboviruses co-occur more often than randomly and found that this may be true for some members of the Flaviviridae and Togaviridae . In conclusion, the development of an assay against a wide diversity of medically relevant arboviruses enabled the analysis of a large sample collection of one of the most abundant African small mammals. Our findings highlight that Mastomys natalensis is involved in the transmission cycle of multiple arboviruses and provide a solid foundation to better understand the role of this ubiquitous rodent in arbovirus outbreaks.

This systematic review aims to assess how different urbanisation patterns related to rapid urban growth, unplanned expansion, and human population density affect the establishment and distribution of Aedes aegypti and Aedes albopictus and create favourable conditions for the spread of dengue, chikungunya, and Zika viruses. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was conducted using the PubMed, Virtual Health Library, Cochrane, WHO Library Database (WHOLIS), Google Scholar, and and the Institutional Repository for Information Sharing (IRIS) databases. From a total of 523 identified studies, 86 were selected for further analysis, and 29 were finally analysed after applying all inclusion and exclusion criteria. The main explanatory variables used to associate urbanisation with epidemiological/entomological outcomes were the following: human population density, urban growth, artificial geographical space, urban construction, and urban density. Associated with the lack of a global definition of urbanisation, several studies provided their own definitions, which represents one of the study's limitations. Results were based on 8 ecological studies/models, 8 entomological surveillance studies, 7 epidemiological surveillance studies, and 6 studies consisting of spatial and predictive models. According to their focus, studies were categorised into 2 main subgroups, namely \"Aedes ecology\" and \"transmission dynamics.\" There was a consistent association between urbanisation and the distribution and density of Aedes mosquitoes in 14 of the studies and a strong relationship between vector abundance and disease transmission in 18 studies. Human population density of more than 1,000 inhabitants per square kilometer was associated with increased levels of arboviral diseases in 15 of the studies. The use of different methods in the included studies highlights the interplay of multiple factors linking urbanisation with ecological, entomological, and epidemiological parameters and the need to consider a variety of these factors for designing effective public health approaches.

In 2021, we screened 91 children in Haiti with acute undifferentiated febrile illness for arbovirus infections. We identified a major outbreak of dengue virus type 2, with 67% of the children testing positive. Two others were positive for chikungunya East/Central/South African IIa subclade, and 2 were positive for Zika virus.

Aedes aegypti and Aedes albopictus are the main vectors of highly pathogenic viruses for humans, such as dengue (DENV), chikungunya (CHIKV), and Zika (ZIKV), which cause febrile, hemorrhagic, and neurological diseases and remain a major threat to global public health. The high ecological plasticity, opportunistic feeding patterns, and versatility in the use of urban and natural breeding sites of these vectors have favored their dispersal and adaptation in tropical, subtropical, and even temperate zones. Due to the lack of available treatments and vaccines, mosquito population control is the most effective way to prevent arboviral diseases. Resident microorganisms play a crucial role in host fitness by preventing or enhancing its vectorial ability to transmit viral pathogens. High-throughput sequencing and metagenomic analyses have advanced our understanding of the composition and functionality of the microbiota of Aedes spp. Interestingly, shotgun metagenomics studies have established that mosquito vectors harbor a highly conserved virome composed of insect-specific viruses (ISV). Although ISVs are not infectious to vertebrates, they can alter different phases of the arboviral cycle, interfering with transmission to the human host. Therefore, this review focuses on the description of Ae. aegypti and Ae. albopictus as vectors susceptible to infection by viral pathogens, highlighting the role of the microbiota-virome in vectorial competence and its potential in control strategies for new emerging and re-emerging arboviruses. Graphical Abstract

We report acute Oropouche virus infections in 2 previously healthy women from a nonendemic region of Brazil outside the Amazon Basin. Infections rapidly progressed to hemorrhagic manifestations and fatal outcomes in 4-5 days. These cases highlight the critical need for enhanced surveillance to clarify epidemiology of this neglected disease.

We report detection of Aedes (Fredwardsius) vittatus mosquitoes in continental North America, in Yucatán, Mexico. Phylogenetic analysis clustered the sequence from mosquitoes collected in Mexico with Caribbean mosquito lineages, suggesting species introduction via the Caribbean. Given its arbovirus competence, urgent inclusion of the Ae. vittatus mosquito in surveillance programs is warranted.

Global risk maps are an important tool for assessing the global threat of mosquito and tick-transmitted arboviral diseases. Public health officials increasingly rely on risk maps to understand the drivers of transmission, forecast spread, identify gaps in surveillance, estimate disease burden, and target and evaluate the impact of interventions. Here, we describe how current approaches to mapping arboviral diseases have become unnecessarily siloed, ignoring the strengths and weaknesses of different data types and methods. This places limits on data and model output comparability, uncertainty estimation and generalisation that limit the answers they can provide to some of the most pressing questions in arbovirus control. We argue for a new generation of risk mapping models that jointly infer risk from multiple data types. We outline how this can be achieved conceptually and show how this new framework creates opportunities to better integrate epidemiological understanding and uncertainty quantification. We advocate for more co-development of risk maps among modellers and end-users to better enable risk maps to inform public health decisions. Prospective validation of risk maps for specific applications can inform further targeted data collection and subsequent model refinement in an iterative manner. If the expanding use of arbovirus risk maps for control is to continue, methods must develop and adapt to changing questions, interventions and data availability.