A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.

Zika virus evolution and spread in the Americas.

Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests.

Role of modelling in COVID-19 policy development.

Models have played an important role in policy development to address the COVID-19 outbreak from its emergence in China to the current global pandemic. Early projections of international spread influenced travel restrictions and border closures. Model projections based on the virus's infectiousness demonstrated its pandemic potential, which guided the global response to and prepared countries for increases in hospitalisations and deaths. Tracking the impact of distancing and movement policies and behaviour changes has been critical in evaluating these decisions. Models have provided insights into the epidemiological differences between higher and lower income countries, as well as vulnerable population groups within countries to help design fit-for-purpose policies. Economic evaluation and policies have combined epidemic models and traditional economic models to address the economic consequences of COVID-19, which have informed policy calls for easing restrictions. Social contact and mobility models have allowed evaluation of the pathways to safely relax mobility restrictions and distancing measures. Finally, models can consider future end-game scenarios, including how suppression can be achieved and the impact of different vaccination strategies.

Modelling insights into the COVID-19 pandemic.

Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that was declared a pandemic by the World Health Organization on 11th March, 2020. Response to this ongoing pandemic requires extensive collaboration across the scientific community in an attempt to contain its impact and limit further transmission. Mathematical modelling has been at the forefront of these response efforts by: (1) providing initial estimates of the SARS-CoV-2 reproduction rate, R0 (of approximately 2-3); (2) updating these estimates following the implementation of various interventions (with significantly reduced, often sub-critical, transmission rates); (3) assessing the potential for global spread before significant case numbers had been reported internationally; and (4) quantifying the expected disease severity and burden of COVID-19, indicating that the likely true infection rate is often orders of magnitude greater than estimates based on confirmed case counts alone. In this review, we highlight the critical role played by mathematical modelling to understand COVID-19 thus far, the challenges posed by data availability and uncertainty, and the continuing utility of modelling-based approaches to guide decision making and inform the public health response. †Unless otherwise stated, all bracketed error margins correspond to the 95% credible interval (CrI) for reported estimates.

The decline of dengue in the Americas in 2017: discussion of multiple hypotheses.

OBJECTIVE: Since the 1980s, dengue incidence has increased 30-fold. However, in 2017, there was a noticeable reduction in reported dengue incidence cases within the Americas, including severe and fatal cases. Understanding the mechanism underlying dengue's incidence and decline in the Americas is vital for public health planning. We aimed to provide plausible explanations for the decline in 2017. METHODS: An expert panel of representatives from scientific and academic institutions, Ministry of Health officials from Latin America and PAHO/WHO staff met in October 2017 to propose hypotheses. The meeting employed six moderated plenary discussions in which participants reviewed epidemiological evidence, suggested explanatory hypotheses, offered their expert opinions on each and developed a consensus. RESULTS: The expert group established that in 2017, there was a generalised decreased incidence, severity and number of deaths due to dengue in the Americas, accompanied by a reduction in reported cases of both Zika and chikungunya virus infections, with no change in distribution among age groups affected. This decline was determined to be unlikely due to changes in epidemiological surveillance systems, as similar designs of surveillance systems exist across the region. Although sudden surveillance disruption is possible at a country or regional level, it is unlikely to occur in all countries simultaneously. Retrospective modelling with epidemiological, immunological and entomological information is needed. Host or immunological factors may have influenced the decline in dengue cases at the population level through immunity; however, herd protection requires additional evidence. Uncertainty remains regarding the effect on the outcome of sequential infections of different dengue virus (DENV) types and Zika virus (ZIKV), and vice versa. Future studies were recommended that examine the epidemiological effect of prior DENV infection on Zika incidence and severity, the epidemiological effect of prior Zika virus infection on dengue incidence and severity, immune correlates based on new-generation ELISA assays, and impact of prior DENV/other arbovirus infection on ZIKV immune response in relation to number of infections and the duration of antibodies in relation to interval of protection. Follow-up studies should also investigate whether increased vector control intensification activities contributed to the decline in transmission of one or more of these arboviruses. Additionally, proposed studies should focus on the potential role of vector competence when simultaneously exposed to various arboviruses, and on entomological surveillance and its impact on circulating vector species, with a goal of applying specific measures that mitigate seasonal occurrence or outbreaks. CONCLUSIONS: Multifactorial events may have accounted for the decline in dengue seen in 2017. Differing elements might explain the reduction in dengue including elements of immunity, increased vector control, and even vector and\or viruses changes or adaptations. Most of the results of this expert consensus group meeting are hypothetical and based on limited evidence. Further studies are needed.

OBJECTIF: Depuis les années 1980, l'incidence de la dengue a été multipliée par 30. Cependant, en 2017, il y a eu une réduction notable du nombre de cas d'incidence de dengue rapportés dans les Amériques. Nous voulions fournir des explications plausibles à la baisse en 2017. MÉTHODES: Un groupe d'experts constitué de représentants d'institutions scientifiques et académiques, d'officiels des Ministères de la Santé d'Amérique Latine et de membres du personnel de l'OPS/OMS s'est réuni en octobre 2017 pour proposer et évaluer des hypothèses. RÉSULTATS: En 2017, il y a eu une baisse généralisée de l'incidence, de la sévérité et du nombre de décès dus à la dengue dans les Amériques, accompagnée d'une réduction des cas rapportés d'infections par le virus Zika et par le virus du chikungunya, sans modification dans la répartition entre les groupes d'âge affectés. Il a été déterminé que ce déclin était peu probablement dû aux changements dans les systèmes de surveillance épidémiologique, étant donné que des systèmes de surveillance similaires existaient dans toute la région. Bien que des perturbations soudaines dans la surveillance soient possibles au niveau national ou régional, il est peu probable que cela se produise simultanément dans tous les pays. Une modélisation rétrospective avec des informations épidémiologiques, immunologiques et entomologiques est nécessaire. Des facteurs liés à l'hôte ou immunologiques peuvent avoir influencé le déclin des cas de dengue au niveau de la population par le biais de l'immunité; cependant, l'évidence d'une protection conférée par l'effet du troupeau nécessite des données supplémentaires. Une incertitude subsiste quant à l'effet sur le résultat des infections séquentielles de différents types du virus de la dengue (DENV) et du virus Zika (ZIKV), et vice-versa. Les études à venir devraient examiner (1) l'effet épidémiologique d'une infection antérieure par le DENV sur l'incidence et la sévérité du virus Zika, (2) l'effet épidémiologique d'une infection antérieure par le virus Zika sur l'incidence et la sévérité de la dengue, (3) les corrélats immunitaires basés sur des tests ELISA de nouvelle génération, (4) l' impact d'une infection antérieure à DENV/autres arbovirus sur la réponse immunitaire au ZIKV en fonction du nombre d'infections et de la durée des anticorps en fonction de l'intervalle de protection, (5) si des activités d'intensification de la lutte antivectorielle ont contribué à la diminution de la transmission d'un ou plusieurs de ces arbovirus, (6) le rôle potentiel de la compétence vectorielle lorsqu'ils sont exposés simultanément à différents arbovirus, (7) la surveillance entomologique et son impact sur la circulation d'espèces de vecteurs, dans le but d'appliquer des mesures spécifiques qui réduisent l'occurrence saisonnière d'épidémies. CONCLUSIONS: Des événements multifactoriels pourraient expliquer le déclin observé de la dengue en 2017. La plupart des résultats de cette réunion du groupe de consensus d'experts sont hypothétiques, reposent sur des données limitées et requièrent des investigations supplémentaires.

Genomic epidemiology supports multiple introductions and cryptic transmission of Zika virus in Colombia.

BACKGROUND: Colombia was the second most affected country during the American Zika virus (ZIKV) epidemic, with over 109,000 reported cases. Despite the scale of the outbreak, limited genomic sequence data were available from Colombia. We sought to sequence additional samples and use genomic epidemiology to describe ZIKV dynamics in Colombia. METHODS: We sequenced ZIKV genomes directly from clinical diagnostic specimens and infected Aedes aegypti samples selected to cover the temporal and geographic breadth of the Colombian outbreak. We performed phylogeographic analysis of these genomes, along with other publicly-available ZIKV genomes from the Americas, to estimate the frequency and timing of ZIKV introductions to Colombia. RESULTS: We attempted PCR amplification on 184 samples; 19 samples amplified sufficiently to perform sequencing. Of these, 8 samples yielded sequences with at least 50% coverage. Our phylogeographic reconstruction indicates two separate introductions of ZIKV to Colombia, one of which was previously unrecognized. We find that ZIKV was first introduced to Colombia in February 2015 (95%CI: Jan 2015 - Apr 2015), corresponding to 5 to 8 months of cryptic ZIKV transmission prior to confirmation in September 2015. Despite the presence of multiple introductions, we find that the majority of Colombian ZIKV diversity descends from a single introduction. We find evidence for movement of ZIKV from Colombia into bordering countries, including Peru, Ecuador, Panama, and Venezuela. CONCLUSIONS: Similarly to genomic epidemiological studies of ZIKV dynamics in other countries, we find that ZIKV circulated cryptically in Colombia. More accurately dating when ZIKV was circulating refines our definition of the population at risk. Additionally, our finding that the majority of ZIKV transmission within Colombia was attributable to transmission between individuals, rather than repeated travel-related importations, indicates that improved detection and control might have succeeded in limiting the scale of the outbreak within Colombia.

Standardized evaluation of Zika nucleic acid tests used in clinical settings and blood screening.

Early detection of Zika virus (ZIKV) transmission within geographic regions informs implementation of community mitigation measures such as vector reduction strategies, travel advisories, enhanced surveillance among pregnant women, and possible implementation of blood and organ donor screening or deferral. Standardized, comparative assessments of ZIKV assay and testing lab performance are important to develop optimal approaches to ZIKV diagnostic testing and surveillance. We conducted an expanded blinded panel study to characterize and compare the analytical performance of fifteen diagnostic and blood screening ZIKV NAT assays, including detection among single- and multiplex assays detecting ZIKV, dengue virus (DENV) and chikungunya virus (CHIKV). A 300 member blinded panel was constructed, consisting of 11 serial half-log dilutions ranging from ~104 to 10-1 genome equivalents/mL in 25 replicates each of the Tahitian Asian ZIKV isolate in ZIKV-negative human serum. Additionally, clinical samples from individuals with DENV-like syndrome or suspected ZIKV infection in Brazil were evaluated. The majority of assays demonstrated good specificity. Analytical sensitivities varied 1-2 logs, with a substantially higher limit of detection (LOD) in one outlier. Similar analytical sensitivity for ZIKV RNA detection in singleplex and multiplex assays of the Grifols and ThermoFisher tests were observed. Coefficient of Assay Efficiency (CE), calculated to characterize assays' RNA extraction and amplification efficiency, ranged from 0.13 for the Certest VIASURE multiplex and 0.75 for the Grifols multiplex assays. In general, assays using transcription mediated amplification (TMA) technology had greater CE compared to assays using conventional PCR technology. Donor screening NAT assays were significantly more sensitive than diagnostic RT-qPCR assays, primarily attributable to higher sample input volumes. However, ideal assays to maximize sensitivity and throughput may not be a viable option in all contexts, with other factors such as cost, instrumentation, and regulatory approval status influencing assay availability and selection, particularly in resource constrained settings.

Vaccine value profile for Chikungunya.

Chikungunya virus (CHIKV) a mosquito-borne alphavirus is the causative agent of Chikungunya (CHIK), a disease with low mortality but high acute and chronic morbidity resulting in a high overall burden of disease. After the acute disease phase, chronic disease including persistent arthralgia is very common, and can cause fatigue and pain that is severe enough to limit normal activities. On average, around 40% of people infected with CHIKV will develop chronic arthritis, which may last for months or years. Recommendations for protection from CHIKV focus on infection control through preventing mosquito proliferation. There is currently no licensed antiviral drug or vaccine against CHIKV. Therefore, one of the most important public health impacts of vaccination would be to decrease burden of disease and economic losses in areas impacted by the virus, and prevent or reduce chronic morbidity associated with CHIK. This benefit would particularly be seen in Low and Middle Income Countries (LMIC) and socio-economically deprived areas, as they are more likely to have more infections and more severe outcomes. This 'Vaccine Value Profile' (VVP) for CHIK is intended to provide a high-level, holistic assessment of the information and data that are currently available to inform the potential public health, economic and societal value of vaccines in the development pipeline and vaccine-like products.This VVP was developed by a working group of subject matter experts from academia, non-profit organizations, public private partnerships, and multi-lateral organizations. All contributors have extensive expertise on various elements of the CHIK VVP and collectively aimed to identify current research and knowledge gaps.The VVP was developed using only existing and publicly available information.

Prevalence of SARS-CoV-2 infection and SARS-CoV-2-specific antibody detection among healthcare workers and hospital staff of a university hospital in Colombia.

Objective: The aim of this study was to determine current and previous SARS-COV-2 infection, and describe risk factors associated with seropositivity, among HCWs and hospital staff between June and October of 2020. Methodology: Data from the day of enrollment for a prospective cohort study were analyzed to determine point prevalence and seroprevalence of SARS-CoV-2 infection in HCWs and hospital staff of a university hospital in Colombia. Respiratory samples were collected to perform RT-PCR tests, along with blood samples to measure SARS-CoV-2 IgM and IgG antibodies. Data on nosocomial and community risk factors for infection were also collected and analyzed. Findings: 420 HCWs and hospital staff members were included. The seroprevalence at baseline was 23.2%, of which 10.7% had only IgM antibodies, 0.7% had IgG, and 11.7% had IgM and IgG. The prevalence of acute SARS-CoV-2 infection was 1.9%. Being a nurse assistant was significantly associated with seropositivity when compared with all other job duties (PR 2.39, 95% CI 1.27-3.65, p = 0.01). Conclusions: Overall SARS-CoV-2 prevalence was 1.9% and seroprevalence was 23.15%. Nurse assistants, medical doctors or students, and laboratory workers had a higher possibility of being SARS-CoV-2 seropositive.

A Review: Aedes-Borne Arboviral Infections, Controls and Wolbachia-Based Strategies.

Arthropod-borne viruses (Arboviruses) continue to generate significant health and economic burdens for people living in endemic regions. Of these viruses, some of the most important (e.g., dengue, Zika, chikungunya, and yellow fever virus), are transmitted mainly by Aedes mosquitoes. Over the years, viral infection control has targeted vector population reduction and inhibition of arboviral replication and transmission. This control includes the vector control methods which are classified into chemical, environmental, and biological methods. Some of these control methods may be largely experimental (both field and laboratory investigations) or widely practised. Perceptively, one of the biological methods of vector control, in particular, Wolbachia-based control, shows a promising control strategy for eradicating Aedes-borne arboviruses. This can either be through the artificial introduction of Wolbachia, a naturally present bacterium that impedes viral growth in mosquitoes into heterologous Aedes aegypti mosquito vectors (vectors that are not natural hosts of Wolbachia) thereby limiting arboviral transmission or via Aedes albopictus mosquitoes, which naturally harbour Wolbachia infection. These strategies are potentially undermined by the tendency of mosquitoes to lose Wolbachia infection in unfavourable weather conditions (e.g., high temperature) and the inhibitory competitive dynamics among co-circulating Wolbachia strains. The main objective of this review was to critically appraise published articles on vector control strategies and specifically highlight the use of Wolbachia-based control to suppress vector population growth or disrupt viral transmission. We retrieved studies on the control strategies for arboviral transmissions via arthropod vectors and discussed the use of Wolbachia control strategies for eradicating arboviral diseases to identify literature gaps that will be instrumental in developing models to estimate the impact of these control strategies and, in essence, the use of different Wolbachia strains and features.

Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study.

BACKGROUND: The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first detected in the city of Wuhan, China has now spread to every inhabitable continent, but now the attention has shifted from China to other epicentres. This study explored early assessment of the influence of spatial proximities and travel patterns from Italy on the further spread of SARS-CoV-2 worldwide. METHODS: Using data on the number of confirmed cases of COVID-19 and air travel data between countries, we applied a stochastic meta-population model to estimate the global spread of COVID-19. Pearson's correlation, semi-variogram, and Moran's Index were used to examine the association and spatial autocorrelation between the number of COVID-19 cases and travel influx (and arrival time) from the source country. RESULTS: We found significant negative association between disease arrival time and number of cases imported from Italy (r = -0.43, p = 0.004) and significant positive association between the number of COVID-19 cases and daily travel influx from Italy (r = 0.39, p = 0.011). Using bivariate Moran's Index analysis, we found evidence of spatial interaction between COVID-19 cases and travel influx (Moran's I = 0.340). Asia-Pacific region is at higher/extreme risk of disease importation from the Chinese epicentre, whereas the rest of Europe, South-America and Africa are more at risk from the Italian epicentre. CONCLUSION: We showed that as the epicentre changes, the dynamics of SARS-CoV-2 spread change to reflect spatial proximities.

Modeling the potential of wAu-Wolbachia strain invasion in mosquitoes to control Aedes-borne arboviral infections.

Arboviral infections such as dengue, Zika and chikungunya are fast spreading diseases that pose significant health problems globally. In order to control these infections, an intracellular bacterium called Wolbachia has been introduced into wild-type mosquito populations in the hopes of replacing the vector transmitting agent, Aedes aegypti with one that is incapable of transmission. In this study, we developed a Wolbachia transmission model for the novel wAu strain which possesses several favourable traits (e.g., enhanced viral blockage and maintenance at higher temperature) but not cyctoplasmic incompatibility (CI)-when a Wolbachia-infected male mosquito mates with an uninfected female mosquito, producing no viable offspring. This model describes the competitive dynamics between wAu-Wolbachia-infected and uninfected mosquitoes and the role of imperfect maternal transmission. By analysing the system via computing the basic reproduction number(s) and stability properties, the potential of the wAu strain as a viable strategy to control arboviral infections is established. The results of this work show that enhanced maintenance of Wolbachia infection at higher temperatures can overcome the lack of CI induction to support wAu-Wolbachia infected mosquito invasion. This study will support future arboviral control programs, that rely on the introduction of new Wolbachia variants.

Impacts of Zika emergence in Latin America on endemic dengue transmission.

In 2015 and 2016, Zika virus (ZIKV) swept through dengue virus (DENV) endemic areas of Latin America. These viruses are of the same family, share a vector and may interact competitively or synergistically through human immune responses. We examine dengue incidence from Brazil and Colombia before, during, and after the Zika epidemic. We find evidence that dengue incidence was atypically low in 2017 in both countries. We investigate whether subnational Zika incidence is associated with changes in dengue incidence and find mixed results. Using simulations with multiple assumptions of interactions between DENV and ZIKV, we find cross-protection suppresses incidence of dengue following Zika outbreaks and low periods of dengue incidence are followed by resurgence. Our simulations suggest correlations in DENV and ZIKV reproduction numbers could complicate associations between ZIKV incidence and post-ZIKV DENV incidence and that periods of low dengue incidence are followed by large increases in dengue incidence.