Understanding the survival of Zika virus in a vector interconnected sexual contact network

Novel 2-indolinone derivatives as promising agents against respiratory syncytial and yellow fever viruses

Background: A vaccine or antiviral drug for respiratory syncytial virus (RSV) infections and a specific antiviral drug for yellow fever virus (YFV) infections has not yet been developed. Method: In this study, 2-indolinone-based N-(4-sulfamoylphenyl)hydrazinecarbothioamides were synthesized. Along with these new compounds, previously synthesized 2-indolinone-based N-(3-sulfamoylphenyl)hydrazinecarbothioamides were evaluated against various DNA and RNA viruses. Results: Some 2-indolinone compounds exhibited nontoxic and selective antiviral activities against RSV and YFV. Halogen substitution at the indole ring increased the anti-RSV activities. Moreover, 1-benzyl and 5-halogen or nitro-substituted compounds were the most effective compounds against YFV. Conclusion: Generally, the 3-sulfonamide-substituted compounds were determined to be more effective than 4-sulfonamide-substituted compounds against RSV and YFV.

Interferon Epsilon Signaling Confers Attenuated Zika Replication in Human Vaginal Epithelial Cells

Zika virus (ZIKV) is an emerging flavivirus that causes congenital birth defects and neurological compilations in the human host. Although ZIKV is primarily transmitted through infected mosquitos, recent studies reveal sexual contact as a potential transmission route. In vagina-bearing individuals, the vaginal epithelium constitutes the first line of defense against viruses. However, it is unclear how ZIKV interacts with the vaginal epithelium to initiate ZIKV transmission. In this study, we demonstrate that exposing ZIKV to human vaginal epithelial cells (hVECs) resulted in de novo viral RNA replication, increased envelope viral protein production, and a steady, extracellular release of infectious viral particles. Interestingly, our data show that, despite an increase in viral load, the hVECs did not exhibit significant cytopathology in culture as other cell types typically do. Furthermore, our data reveal that the innate antiviral state of hVECs plays a crucial role in preventing viral cytopathology. For the first time, our data show that interferon epsilon inhibits ZIKV replication. Collectively, our results in this study provide a novel perspective on the viral susceptibility and replication dynamics during ZIKV infection in the human vaginal epithelium. These findings will be instrumental towards developing therapeutic agents aimed at eliminating the pathology caused by the virus.

A Novel Series of Indole Alkaloid Derivatives Inhibit Dengue and Zika Virus Infection by Interference with the Viral Replication Complex

Here, we identified a novel class of compounds which demonstrated good antiviral activity against dengue and Zika virus infection. These derivatives constitute intermediates in the synthesis of indole (ervatamine-silicine) alkaloids and share a tetracyclic structure, with an indole and a piperidine fused to a seven-membered carbocyclic ring. Structure-activity relationship studies indicated the importance of substituent at position C-6 and especially the presence of a benzyl ester for the activity and cytotoxicity of the molecules. In addition, the stereochemistry at C-7 and C-8, as well as the presence of an oxazolidine ring, influenced the potency of the compounds. Mechanism of action studies with two analogues of this family (compounds 22 and trans-14) showed that this class of molecules can suppress viral infection during the later stages of the replication cycle (RNA replication/assembly). Moreover, a cell-dependent antiviral profile of the compounds against several Zika strains was observed, possibly implying the involvement of a cellular factor(s) in the activity of the molecules. Sequencing of compound-resistant Zika mutants revealed a single nonsynonymous amino acid mutation (aspartic acid to histidine) at the beginning of the predicted transmembrane domain 1 of NS4B protein, which plays a vital role in the formation of the viral replication complex. To conclude, our study provides detailed information on a new class of NS4B-associated inhibitors and strengthens the importance of identifying host-virus interactions in order to tackle flavivirus infections.

Risk Assessment of Dengue Transmission in Bangladesh Using a Spatiotemporal Network Model and Climate Data

Vector-borne disease risk assessment is crucial to optimize surveillance, preventative measures (vector control), and resource allocation (medical supplies). High arthropod abundance and host interaction strongly correlate to vector-borne pathogen transmission. Increasing host density and movement increases the possibility of local and long-distance pathogen transmission. Therefore, we developed a risk-assessment framework using climate (average temperature and rainfall) and host demographic (host density and movement) data, particularly suitable for regions with unreported or underreported incidence data. This framework consisted of a spatiotemporal network-based approach coupled with a compartmental disease model and nonhomogeneous Gillespie algorithm. The correlation of climate data with vector abundance and host–vector interactions is expressed as vectorial capacity—a parameter that governs the spreading of infection from an infected host to a susceptible one via vectors. As an example, the framework is applied for dengue in Bangladesh. Vectorial capacity is inferred for each week throughout a year using average monthly temperature and rainfall data. Long-distance pathogen transmission is expressed with human movement data in the spatiotemporal network. We have identified the spatiotemporal suitability of dengue spreading in Bangladesh as well as the significant-incidence window and peak-incidence period. Analysis of yearly dengue data variation suggests the possibility of a significant outbreak with a new serotype introduction. The outcome of the framework comprised spatiotemporal suitability maps and probabilistic risk maps for spatial infection spreading. This framework is capable of vector-borne disease risk assessment without historical incidence data and can be a useful tool for preparedness with accurate human movement data.

Generation of swine movement network and analysis of efficient mitigation strategies for African swine fever virus

Animal movement networks are essential in understanding and containing the spread of infectious diseases in farming industries. Due to its confidential nature, movement data for the US swine farming population is not readily available. Hence, we propose a method to generate such networks from limited data available in the public domain. As a potentially devastating candidate, we simulate the spread of African swine fever virus (ASFV) in our generated network and analyze how the network structure affects the disease spread. We find that high in-degree farm operations (i.e., markets) play critical roles in the disease spread. We also find that high in-degree based targeted isolation and hypothetical vaccinations are more effective for disease control compared to other centrality-based mitigation strategies. The generated networks can be made more robust by validation with more data whenever more movement data will be available.

Hiding in plain sight: an evolutionary approach to the South American Zika outbreak and its future consequences

Emerging Infectious Diseases (EID) pose a world-wide health and socio-economic threat. Accelerating climate change and globalization are exposing unforeseen ways that pathogens cope with their surroundings. The 2015 Zika virus (ZIKV) outbreak was an example of expansion into previously inaccessible fitness spaces, causing a sudden epidemic. Recent studies indicating the subsequent decrease in symptomatic cases means the virus is in remission, currently poses little threat, and therefore can be ignored. We present an evolutionary scenario derived from the Stockholm Paradigm, of oscillating phases of expansion and isolation, accompanied by changes in transmission, persistence, virulence, and pathology. Chief among these is the likelihood that asymptomatic strains are constantly transmitted sexually. This suggests that the currently quiescent virus retains capacities to reemerge abruptly and spread rapidly in an arena of changing opportunity.

Risk assessment of Ebola virus disease spreading in Uganda using a two-layer temporal network

Network-based modelling of infectious diseases apply compartmental models on a contact network, which makes the epidemic process crucially dependent on the network structure. For highly contagious diseases such as Ebola virus disease (EVD), interpersonal contact plays the most vital role in human-to-human transmission. Therefore, for accurate representation of EVD spreading, the contact network needs to resemble the reality. Prior research has mainly focused on static networks (only permanent contacts) or activity-driven networks (only temporal contacts) for Ebola spreading. A comprehensive network for EVD spreading should include both these network structures, as there are always some permanent contacts together with temporal contacts. Therefore, we propose a two-layer temporal network for Uganda, which is at risk of an Ebola outbreak from the neighboring Democratic Republic of Congo (DRC) epidemic. The network has a permanent layer representing permanent contacts among individuals within the family level, and a data-driven temporal network for human movements motivated by cattle trade, fish trade, or general communications. We propose a Gillespie algorithm with the susceptible-infected-recovered (SIR) compartmental model to simulate the evolution of EVD spreading as well as to evaluate the risk throughout our network. As an example, we applied our method to a network consisting of 23 districts along different movement routes in Uganda starting from bordering districts of the DRC to Kampala. Simulation results show that some regions are at higher risk of infection, suggesting some focal points for Ebola preparedness and providing direction to inform interventions in the field. Simulation results also show that decreasing physical contact as well as increasing preventive measures result in a reduction of chances to develop an outbreak. Overall, the main contribution of this paper lies in the novel method for risk assessment, which can be more precise with an increasing volume of accurate data for creating the network model.