EPIDEMIOLOGY. Countering the Zika epidemic in Latin America

Policy impact of the Imperial College COVID-19 Response Team: global perspective and United Kingdom case study

BACKGROUND

Mathematical models and advanced analytics play an important role in policy decision making and mobilizing action. The Imperial College Coronavirus Disease 2019 (COVID-19) Response Team (ICCRT) provided continuous, timely and robust epidemiological analyses to inform the policy responses of governments and public health agencies around the world. This study aims to quantify the policy impact of ICCRT outputs, and understand which evidence was considered policy-relevant during the COVID-19 pandemic.

METHODS

We collated all outputs published by the ICCRT between 01-01-2020 and 24-02-2022 and conducted inductive thematic analysis. A systematic search of the Overton database identified policy document references, as an indicator of policy impact.

RESULTS

We identified 620 outputs including preprints (16%), reports (29%), journal articles (37%) and news items (18%). More than half (56%) of all reports and preprints were subsequently peer-reviewed and published as a journal article after 202 days on average. Reports and preprints were crucial during the COVID-19 pandemic to the timely distribution of important research findings. One-fifth of ICCRT outputs (21%) were available to or considered by United Kingdom government meetings. Policy documents from 41 countries in 26 different languages referenced 43% of ICCRT outputs, with a mean time between publication and reference in the policy document of 256 days. We analysed a total of 1746 policy document references. Two-thirds (61%) of journal articles, 39% of preprints, 31% of reports and 16% of news items were referenced in one or more policy documents (these 217 outputs had a mean of 8 policy document references per output). The most frequent themes of the evidence produced by the ICCRT reflected the evidence-need for policy decision making, and evolved accordingly from the pre-vaccination phase [severity, healthcare demand and capacity, and non-pharmaceutical interventions (NPIs)] to the vaccination phase of the epidemic (variants and genomics).

CONCLUSION

The work produced by the ICCRT affected global and domestic policy during the COVID-19 pandemic. The focus of evidence produced by the ICCRT corresponded with changing policy needs over time. The policy impact from ICCRT news items highlights the effectiveness of this unique communication strategy in addition to traditional research outputs, ensuring research informs policy decisions more effectively.

Best practices for estimating and reporting epidemiological delay distributions of infectious diseases

Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strategies. In recent work, we found that censoring, right truncation, and dynamical bias were rarely addressed correctly when estimating delays and that these biases were large enough to have knock-on impacts across a large number of use cases. Here, we formulate a checklist of best practices for estimating and reporting epidemiological delays. We also provide a flowchart to guide practitioners based on their data. Our examples are focused on the incubation period and serial interval due to their importance in outbreak response and modeling, but our recommendations are applicable to other delays. The recommendations, which are based on the literature and our experience estimating epidemiological delay distributions during outbreak responses, can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses.

Herd immunity to endemic diseases: Historical concepts and implications for public health policy

BACKGROUND

"Herd immunity" became a contested term during the COVID-19 pandemic. Although the term "herd immunity" is often used to refer to thresholds at which some diseases can be eliminated (e.g., due to mass vaccination), the term has multiple referents. Different concepts of herd immunity have been relevant throughout the history of immunology and infectious disease epidemiology. For some diseases, herd immunity plays a role in the development of an endemic equilibrium, rather than elimination via threshold effects.

METHODS

We reviewed academic literature from 1920 to 2022, using historical and philosophical analysis to identify and develop relevant concepts of herd immunity.

RESULTS

This paper analyses the ambiguity surrounding the concept of herd immunity during the pandemic. We argue for the need to recapture a long-standing interpretation of this concept as one of the factors that leads to a dynamic endemic equilibrium between a host population and a mutating respiratory pathogen.

CONCLUSIONS

Informed by the history of infectious disease epidemiology, we argue that understanding the concept in this way will help us manage both SARS-CoV-2 and hundreds of other seasonal respiratory pathogens with which we live but which have been disrupted due to sustained public health measures/non-pharmaceutical interventions targeting SARS-CoV-2.

Investigating the antiviral therapeutic potentialities of marine polycyclic lamellarin pyrrole alkaloids as promising inhibitors for SARS-CoV-2 and Zika main proteases (Mpro)

The new coronavirus variant (SARS-CoV-2) and Zika virus are two world-wide health pandemics. Along history, natural products-based drugs have always crucially recognized as a main source of valuable medications. Considering the SARS-CoV-2 and Zika main proteases (Mpro) as the re-production key element of the viral cycle and its main target, herein we report an intensive computer-aided virtual screening for a focused list of 39 marine lamellarins pyrrole alkaloids, against SARS-CoV-2 and Zika main proteases (Mpro) using a set of combined modern computational methodologies including molecular docking (MDock), molecule dynamic simulations (MDS) and structure-activity relationships (SARs) as well. Indeed, the molecular docking studies had revealed four promising marine alkaloids including [lamellarin H (14)/K (17)] and [lamellarin S (26)/Z (39)], according to their notable ligand-protein energy scores and relevant binding affinities with the SARS-CoV-2 and Zika (Mpro) pocket residues, respectively. Consequentially, these four chemical hits were further examined thermodynamically though investigating their MD simulations at 100 ns, where they showed prominent stability within the accommodated (Mpro) pockets. Moreover, in-deep SARs studies suggested the crucial roles of the rigid fused polycyclic ring system, particularly aromatic A- and F- rings, position of the phenolic -OH and δ-lactone functionalities as essential structural and pharmacophoric features. Finally, these four promising lamellarins alkaloids were investigated for their in-silico ADME using the SWISS ADME platform, where they displayed appropriated drug-likeness properties. Such motivating outcomes are greatly recommending further in vitro/vivo examinations regarding those lamellarins pyrrole alkaloids (LPAs).Communicated by Ramaswamy H. Sarma.

Zika Virus-A Reemerging Neurotropic Arbovirus Associated with Adverse Pregnancy Outcomes and Neuropathogenesis

Zika virus (ZIKV) is a reemerging flavivirus that is primarily spread through bites from infected mosquitos. It was first discovered in 1947 in sentinel monkeys in Uganda and has since been the cause of several outbreaks, primarily in tropical and subtropical areas. Unlike earlier outbreaks, the 2015-2016 epidemic in Brazil was characterized by the emergence of neurovirulent strains of ZIKV strains that could be sexually and perinatally transmitted, leading to the Congenital Zika Syndrome (CZS) in newborns, and Guillain-Barre Syndrome (GBS) along with encephalitis and meningitis in adults. The immune response elicited by ZIKV infection is highly effective and characterized by the induction of both ZIKV-specific neutralizing antibodies and robust effector CD8+ T cell responses. However, the structural similarities between ZIKV and Dengue virus (DENV) lead to the induction of cross-reactive immune responses that could potentially enhance subsequent DENV infection, which imposes a constraint on the development of a highly efficacious ZIKV vaccine. The isolation and characterization of antibodies capable of cross-neutralizing both ZIKV and DENV along with cross-reactive CD8+ T cell responses suggest that vaccine immunogens can be designed to overcome these constraints. Here we review the structural characteristics of ZIKV along with the evidence of neuropathogenesis associated with ZIKV infection and the complex nature of the immune response that is elicited by ZIKV infection.

Evidence of Zika Virus Reinfection by Genome Diversity and Antibody Response Analysis, Brazil

We generated 238 Zika virus (ZIKV) genomes from 135 persons in Brazil who had samples collected over 1 year to evaluate virus persistence. Phylogenetic inference clustered the genomes together with previously reported ZIKV strains from northern Brazil, showing that ZIKV has been remained relatively stable over time. Temporal phylogenetic analysis revealed limited within-host diversity among most ZIKV-persistent infected associated samples. However, we detected unusual virus temporal diversity from >5 persons, uncovering the existence of divergent genomes within the same patient. All those patients showed an increase in neutralizing antibody levels, followed by a decline at the convalescent phase of ZIKV infection. Of interest, in 3 of those patients, titers of neutralizing antibodies increased again after 6 months of ZIKV infection, concomitantly with real-time reverse transcription PCR re-positivity, supporting ZIKV reinfection events. Altogether, our findings provide evidence for the existence of ZIKV reinfection events.

Chikungunya: a decade of burden in the Americas

In the Americas, one decade following its emergence in 2013, chikungunya virus (CHIKV) continues to spread and cause epidemics across the region. To date, 3.7 million suspected and laboratory-confirmed chikungunya cases have been reported in 50 countries or territories in the Americas. Here, we outline the current status and epidemiological aspects of chikungunya in the Americas and discuss prospects for future research and public health strategies to combat CHIKV in the region.

Impact of Ebola and COVID-19 on maternal, neonatal, and child health care among populations affected by conflicts: a scoping review exploring demand and supply-side barriers and solutions

INTRODUCTION

Armed conflicts have a severe impact on the health of women and children. Global health emergencies such as pandemics and disease outbreaks further exacerbate the challenges faced by vulnerable populations in accessing maternal, neonatal, and child healthcare (MNCH). There is a lack of evidence that summarizes the challenges faced by conflict-affected pregnant women, mothers, and children in accessing MNCH services during global health emergencies, mainly the Ebola and COVID-19 pandemics. This scoping review aimed to analyze studies evaluating and addressing barriers to accessing comprehensive MNCH services during Ebola and COVID-19 emergencies in populations affected by conflict.

METHODS

The search was conducted on PubMed, Scopus, and Web of Science databases using terms related to Ebola and COVID-19, conflicts, and MNCH. Original studies published between 1990 and 2022 were retrieved. Articles addressing the challenges in accessing MNCH-related services during pandemics in conflict-affected settings were included. Thematic analysis was performed to categorize the findings and identify barriers and solutions.

RESULTS

Twenty-nine studies met the inclusion criteria. Challenges were identified in various MNCH domains, including antenatal care, intrapartum care, postnatal care, vaccination, family planning, and the management of childhood illnesses. Ebola-related supply-side challenges mainly concerned accessibility issues, health workforce constraints, and the adoption of stringent protocols. COVID-19 has resulted in barriers related to access to care, challenges pertaining to the health workforce, and new service adoption. On the demand-side, Ebola- and COVID-19-related risks and apprehensions were the leading barriers in accessing MNCH care. Community constraints on utilizing services during Ebola were caused by a lack of trust and awareness. Demand-side challenges of COVID-19 included fear of disease, language barriers, and communication difficulties. Strategies such as partnerships, strengthening of health systems, service innovation, and community-based initiatives have been employed to overcome these barriers.

CONCLUSION

Global health emergencies amplify the barriers to accessing MNCH services faced by conflict-affected populations. Cultural, linguistic, and supply-side factors are key challenges affecting various MNCH domains. Community-sensitive initiatives enhancing primary health care (PHC), mobile clinics, or outreach programs, and the integration of MNCH into PHC delivery should be implemented. Efforts should prioritize the well-being and empowerment of vulnerable populations. Addressing these barriers is crucial for achieving universal health coverage and the Sustainable Development Goals.

Estimating the potential risk of transmission of arboviruses in the Americas and Europe: a modelling study

BACKGROUND

Estimates of the spatiotemporal distribution of different mosquito vector species and the associated risk of transmission of arboviruses are key to design adequate policies for preventing local outbreaks and reducing the number of human infections in endemic areas. In this study, we quantified the abundance of Aedes albopictus and Aedes aegypti and the local transmission potential for three arboviral infections at an unprecedented spatiotemporal resolution in areas where no entomological surveillance is available.

METHODS

We developed a computational model to quantify the daily abundance of Aedes mosquitoes, leveraging temperature and precipitation records. The model was calibrated on mosquito surveillance data collected in 115 locations in Europe and the Americas between 2007 and 2018. Model estimates were used to quantify the reproduction number of dengue virus, Zika virus, and chikungunya in Europe and the Americas, at a high spatial resolution.

FINDINGS

In areas colonised by both Aedes species, A aegypti was estimated to be the main vector for the transmission of dengue virus, Zika virus, and chikungunya, being associated with a higher estimate of R0 when compared with A albopictus. Our estimates highlighted that these arboviruses were endemic in tropical and subtropical countries, with the highest risks of transmission found in central America, Venezuela, Colombia, and central-east Brazil. A non-negligible potential risk of transmission was also estimated for Florida, Texas, and Arizona (USA). The broader ecological niche of A albopictus could contribute to the emergence of chikungunya outbreaks and clusters of dengue autochthonous cases in temperate areas of the Americas, as well as in mediterranean Europe (in particular, in Italy, southern France, and Spain).

INTERPRETATION

Our results provide a comprehensive overview of the transmission potential of arboviral diseases in Europe and the Americas, highlighting areas where surveillance and mosquito control capacities should be prioritised.

FUNDING

EU and Ministero dell'Università e della Ricerca, Italy (Piano Nazionale di Ripresa e Resilienza Extended Partnership initiative on Emerging Infectious Diseases); EU (Horizon 2020); Ministero dell'Università e della Ricerca, Italy (Progetti di ricerca di Rilevante Interesse Nazionale programme); Brazilian National Council of Science, Technology and Innovation; Ministry of Health, Brazil; and Foundation of Research for Minas Gerais, Brazil.

Seroprevalence of Zika in Brazil stratified by age and geographic distribution

Congenital Zika is a devastating consequence of maternal Zika virus infections. Estimates of age-dependent seroprevalence profiles are central to our understanding of the force of Zika virus infections. We set out to calculate the age-dependent seroprevalence of Zika virus infections in Brazil. We analyzed serum samples stratified by age and geographic location, collected from 2016 to 2019, from about 16,000 volunteers enrolled in a Phase 3 dengue vaccine trial led by the Institute Butantan in Brazil. Our results show that Zika seroprevalence has a remarkable age-dependent and geographical distribution, with an average age of the first infection varying from region to region, ranging from 4.97 (3.03–5.41) to 7.24 (6.98–7.90) years. The calculated basic reproduction number, , varied from region to region, ranging from 1.18 (1.04–1.41) to 2.33 (1.54–3.85). Such data are paramount to determine the optimal age to vaccinate against Zika, if and when such a vaccine becomes available.

Estimating the epidemic reproduction number from temporally aggregated incidence data: A statistical modelling approach and software tool

The time-varying reproduction number (Rt) is an important measure of epidemic transmissibility that directly informs policy decisions and the optimisation of control measures. EpiEstim is a widely used opensource software tool that uses case incidence and the serial interval (SI, time between symptoms in a case and their infector) to estimate Rt in real-time. The incidence and the SI distribution must be provided at the same temporal resolution, which can limit the applicability of EpiEstim and other similar methods, e.g. for contexts where the time window of incidence reporting is longer than the mean SI. In the EpiEstim R package, we implement an expectation-maximisation algorithm to reconstruct daily incidence from temporally aggregated data, from which Rt can then be estimated. We assess the validity of our method using an extensive simulation study and apply it to COVID-19 and influenza data. For all datasets, the influence of intra-weekly variability in reported data was mitigated by using aggregated weekly data. Rt estimated on weekly sliding windows using incidence reconstructed from weekly data was strongly correlated with estimates from the original daily data. The simulation study revealed that Rt was well estimated in all scenarios and regardless of the temporal aggregation of the data. In the presence of weekend effects, Rt estimates from reconstructed data were more successful at recovering the true value of Rt than those obtained from reported daily data. These results show that this novel method allows Rt to be successfully recovered from aggregated data using a simple approach with very few data requirements. Additionally, by removing administrative noise when daily incidence data are reconstructed, the accuracy of Rt estimates can be improved.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Allosteric quinoxaline-based inhibitors of the flavivirus NS2B/NS3 protease

Viruses from the Flavivirus genus infect millions of people worldwide and cause severe diseases, including recent epidemics of dengue virus (DENV), and Zika virus (ZIKV). There is currently no antiviral treatment against flavivirus infections, despite considerable efforts to develop inhibitors against essential viral enzymes including NS2B/NS3 protease. Targeting the flavivirus NS2B/NS3 protease proved to be challenging because of the conformational dynamics, topology, and electrostatic properties of the active site. Here, we report the identification of quinoxaline-based allosteric inhibitors by fragment-based drug discovery approach as a promising new drug-like scaffold to target the NS2B/NS3 protease. Enzymatic assays and mutational analysis of the allosteric site in ZIKV NS2B/NS3 protease support noncompetitive inhibition mechanism as well as engineered DENV protease construct indicating the compounds likely compete with the NS2B cofactor for binding to the protease domain. Furthermore, antiviral activity confirmed the therapeutic potential of this new inhibitor scaffold.

Suppression of flavivirus transmission from animal hosts to mosquitoes with a mosquito-delivered vaccine

Zoonotic viruses circulate in the natural reservoir and sporadically spill over into human populations, resulting in endemics or pandemics. We previously found that the Chaoyang virus (CYV), an insect-specific flavivirus (ISF), is replication-defective in vertebrate cells. Here, we develope a proof-of-concept mosquito-delivered vaccine to control the Zika virus (ZIKV) within inaccessible wildlife hosts using CYV as the vector. The vaccine is constructed by replacing the pre-membrane and envelope (prME) proteins of CYV with those of ZIKV, assigned as CYV-ZIKV. CYV-ZIKV replicates efficiently in Aedes mosquitoes and disseminates to the saliva, with no venereal or transovarial transmission observed. To reduce the risk of CYV-ZIKV leaking into the environment, mosquitoes are X-ray irradiated to ensure 100% infertility, which does not affect the titer of CYV-ZIKV in the saliva. Immunization of mice via CYV-ZIKV-carrying mosquito bites elicites robust and persistent ZIKV-specific immune responses and confers complete protection against ZIKV challenge. Correspondingly, the immunized mice could no longer transmit the challenged ZIKV to naïve mosquitoes. Therefore, immunization with an ISF-vectored vaccine via mosquito bites is feasible to induce herd immunity in wildlife hosts of ZIKV. Our study provides a future avenue for developing a mosquito-delivered vaccine to eliminate zoonotic viruses in the sylvatic cycle.

Climate-driven mosquito-borne viral suitability index: measuring risk transmission of dengue, chikungunya and Zika in Mexico

Background

Climate variability influences the population dynamics of the Aedes aegypti mosquito that transmits the viruses that cause dengue, chikungunya and Zika. In recent years these diseases have grown considerably. Dengue is now the fastest-growing mosquito-transmitted disease worldwide, putting 40 per cent of the global population at risk. With no effective antiviral treatments or vaccines widely available, controlling mosquito population remains one of the most effective ways to prevent epidemics. This paper analyses the temporal and spatial dynamics of dengue in Mexico during 2000–2020 and that of chikungunya and Zika since they first appeared in the country in 2014 and 2015, respectively. This study aims to evaluate how seasonal climatological variability affects the potential risk of transmission of these mosquito-borne diseases. Mexico is among the world’s most endemic countries in terms of dengue. Given its high incidence of other mosquito-borne diseases and its size and wide range of climates, it is a good case study.

Methods

We estimate the recently proposed mosquito-borne viral suitability index P, which measures the transmission potential of mosquito-borne pathogens. This index mathematically models how humidity, temperature and precipitation affect the number of new infections generated by a single infected adult female mosquito in a host population. We estimate this suitability index across all Mexico, at small-area level, on a daily basis during 2000–2020.

Results

We find that the index P predicted risk transmission is strongly correlated with the areas and seasons with a high incidence of dengue within the country. This correlation is also high enough for chikungunya and Zika in Mexico. We also show the index P is sensitive to seasonal climatological variability, including extreme weather shocks.

Conclusions

The paper shows the dynamics of dengue, chikungunya and Zika in Mexico are strongly associated with seasonal climatological variability and the index P. This potential risk of transmission index, therefore, is a valuable tool for surveillance for mosquito-borne diseases, particularly in settings with varied climates and limited entomological capacity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00317-0.

Reformulating the susceptible-infectious-removed model in terms of the number of detected cases: well-posedness of the observational model

Compartmental models are popular in the mathematics of epidemiology for their simplicity and wide range of applications. Although they are typically solved as initial value problems for a system of ordinary differential equations, the observed data are typically akin to a boundary value-type problem: we observe some of the dependent variables at given times, but we do not know the initial conditions. In this paper, we reformulate the classical susceptible-infectious-recovered system in terms of the number of detected positive infected cases at different times to yield what we term the observational model. We then prove the existence and uniqueness of a solution to the boundary value problem associated with the observational model and present a numerical algorithm to approximate the solution. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Socioeconomic risk markers of congenital Zika syndrome: a nationwide, registry-based study in Brazil

While it is well known that socioeconomic markers are associated with a higher risk of arbovirus infections, research on the relationship between socioeconomic factors and congenital Zika syndrome (CZS) remains limited. This study investigates the relationship between socioeconomic risk markers and live births with CZS in Brazil. We conducted a population-based study using data from all registered live births in Brazil (Live Births Information System) linked with the Public Health Event Record from 1 January 2015 to 31 December 2018. We used logistic regression models to estimate the OR and 95% CIs of CZS based on a three-level framework. In an analysis of 11 366 686 live births, of which 3353 had CZS, we observed that live births of self-identified black or mixed race/brown mothers (1.72 (95% CI 1.47 to 2.01) and 1.37 (95% CI 1.24 to 1.51)) were associated with a higher odds of CZS. Live births from single women compared with married women and those from women with less than 12 years of education compared with those with more than 12 years of education also had higher odds of CZS. In addition, live births following fewer prenatal care appointments had increased odds of CZS in the nationwide data. However, in the analyses conducted in the Northeast region (where the microcephaly epidemic started before the link with Zika virus was established and before preventive measures were known or disseminated), no statistical association was found between the number of prenatal care appointments and the odds of CZS. This study shows that live births of the most socially vulnerable women in Brazil had the greatest odds of CZS. This disproportionate distribution of risk places an even greater burden on already socioeconomically disadvantaged groups, and the lifelong disabilities caused by this syndrome may reinforce existing social and health inequalities.

Model-Based Projection of Zika Infection Risk with Temperature Effect: A Case Study in Southeast Asia

Zika virus (ZIKV) recently reemerged in the Americas and rapidly expanded in global range. It is posing significant concerns of public health due to its link to birth defects and its complicated transmission routes. Southeast Asia is badly hit by ZIKV, but limited information was found on the transmission potential of ZIKV in the region. In this paper, we develop a new dynamic process-based mathematical model, which incorporates the interactions among humans (sexual transmissibility), and between human and mosquitoes (biting transmissibility), as well as the essential impacts of temperature. The model is first validated by fitting the 2016 ZIKV outbreak in Singapore via Markov chain Monte Carlo method. Based on that, we demonstrate the effects of temperature on mosquito ecology and ZIKV transmission, and further clarify the potential risk of ZIKV outbreak in Southeast Asian countries. The results show that (i) the estimated infection reproduction number [Formula: see text] in Singapore fell from 6.93 (in which the contribution of sexual transmission was 0.89) to 0.24 after the deployment of control strategies; (ii) the optimal temperature for the reproduction of ZIKV infections and adult mosquitoes are estimated to be [Formula: see text]C and [Formula: see text]C, respectively; and (iii) the [Formula: see text] in Southeast Asia could be between 3 and 7, with an inverted-U shape around the year. The large values of [Formula: see text] and the simulative patterns of ZIKV transmission in each country highlights the high risk of ZIKV attack in Southeast Asia.

Comparing sources of mobility for modelling the epidemic spread of Zika virus in Colombia

Timely, accurate, and comparative data on human mobility is of paramount importance for epidemic preparedness and response, but generally not available or easily accessible. Mobile phone metadata, typically in the form of Call Detail Records (CDRs), represents a powerful source of information on human movements at an unprecedented scale. In this work, we investigate the potential benefits of harnessing aggregated CDR-derived mobility to predict the 2015-2016 Zika virus (ZIKV) outbreak in Colombia, when compared to other traditional data sources. To simulate the spread of ZIKV at sub-national level in Colombia, we employ a stochastic metapopulation epidemic model for vector-borne diseases. Our model integrates detailed data on the key drivers of ZIKV spread, including the spatial heterogeneity of the mosquito abundance, and the exposure of the population to the virus due to environmental and socio-economic factors. Given the same modelling settings (i.e. initial conditions and epidemiological parameters), we perform in-silico simulations for each mobility network and assess their ability in reproducing the local outbreak as reported by the official surveillance data. We assess the performance of our epidemic modelling approach in capturing the ZIKV outbreak both nationally and sub-nationally. Our model estimates are strongly correlated with the surveillance data at the country level (Pearson’s r = 0.92 for the CDR-informed network). Moreover, we found strong performance of the model estimates generated by the CDR-informed mobility networks in reproducing the local outbreak observed at the sub-national level. Compared to the CDR-informed networks, the performance of the other mobility networks is either comparatively similar or substantially lower, with no added value in predicting the local epidemic. This suggests that mobile phone data captures a better picture of human mobility patterns. This work contributes to the ongoing discussion on the value of aggregated mobility estimates from CDRs data that, with appropriate data protection and privacy safeguards, can be used for social impact applications and humanitarian action.

Riboflavin, a Potent Neuroprotective Vitamin: Focus on Flavivirus and Alphavirus Proteases

Several neurotropic viruses are members of the flavivirus and alphavirus families. Infections caused by these viruses may cause long-term neurological sequelae in humans. The continuous emergence of infections caused by viruses around the world, such as the chikungunya virus (CHIKV) (Alphavirus genus), the zika virus (ZIKV) and the yellow fever virus (YFV) (both of the Flavivirus genus), warrants the development of new strategies to combat them. Our study demonstrates the inhibitory potential of the water-soluble vitamin riboflavin against NS2B/NS3pro of ZIKV and YFV and nsP2pro of CHIKV. Riboflavin presents a competitive inhibition mode with IC50 values in the medium µM range of 79.4 ± 5.0 µM for ZIKV NS2B/NS3pro and 45.7 ± 2.9 μM for YFV NS2B/NS3pro. Against CHIKV nsP2pro, the vitamin showed a very strong effect (93 ± 5.7 nM). The determined dissociation constants (KD) are significantly below the threshold value of 30 µM. The ligand binding increases the thermal stability between 4 °C and 8 °C. Unexpectedly, riboflavin showed inhibiting activity against another viral protein; the molecule was also able to inhibit the viral entry of CHIKV. Molecular dynamics simulations indicated great stability of riboflavin in the protease active site, which validates the repurposing of riboflavin as a promising molecule in drug development against the viruses presented here.

Seroepidemiological Reconstruction of Long-term Chikungunya Virus Circulation in Burkina Faso and Gabon

Chikungunya virus (CHIKV) is a major public health concern worldwide. However, infection levels are rarely known, especially in Africa. We recruited individuals from Ouagadougou, Burkina Faso and Lambaréné, Gabon (age range, 1-55 years), tested their blood for CHIKV antibodies, and used serocatalytic models to reconstruct epidemiological histories. In Ouagadougou, 291 of 999 (29.1%) individuals were seropositive, ranging from 2% among those aged <10 years to 66% in those aged 40-55 years. We estimated there were 7 outbreaks since the 1970s but none since 2001, resulting in 600 000 infections in the city, none of which were reported. However, we could not definitively conclude whether infections were due to CHIKV or o'nyong-nyong, another alphavirus. In Lambaréné, 117 of 427 (27%) participants were seropositive. Our model identified a single outbreak sometime since 2007, consistent with the only reported CHIKV outbreak in the country. These findings suggest sporadic outbreaks in these settings and that the burden remains undetected or incorrectly attributed.

Socioeconomic disparities associated with symptomatic Zika virus infections in pregnancy and congenital microcephaly: A spatiotemporal analysis from Goiânia, Brazil (2016 to 2020)

The Zika virus (ZIKV) epidemic, which was followed by an unprecedented outbreak of congenital microcephaly, emerged in Brazil unevenly, with apparent pockets of susceptibility. The present study aimed to detect high-risk areas for ZIKV infection and microcephaly in Goiania, a large city of 1.5 million inhabitants in Central-West Brazil. Using geocoded surveillance data from the Brazilian Information System for Notifiable Diseases (SINAN) and from the Public Health Event Registry (RESP-microcefalia), we analyzed the spatiotemporal distribution and socioeconomic indicators of laboratory confirmed (RT-PCR and/or anti-ZIKV IgM ELISA) symptomatic ZIKV infections among pregnant women and clinically confirmed microcephaly in neonates, from 2016 to 2020. We investigated temporal patterns by estimating the risk of symptomatic maternal ZIKV infections and microcephaly per 1000 live births per month. We examined the spatial distribution of maternal ZIKV infections and microcephaly cases across the 63 subdistricts of Goiania by manually plotting the geographical coordinates. We used spatial scan statistics estimated by discrete Poisson models to detect high clusters of maternal ZIKV infection and microcephaly and compared the distributions by socioeconomic indicators measured at the subdistrict level. In total, 382 lab-confirmed cases of maternal ZIKV infections, and 31 cases of microcephaly were registered in the city of Goiania. More than 90% of maternal cases were reported between 2016 and 2017. The highest incidence of ZIKV cases among pregnant women occurred between February and April 2016. A similar pattern was observed in the following year, although with a lower number of cases, indicating seasonality for ZIKV infection, during the local rainy season. Most congenital microcephaly cases occurred with a time-lag of 6 to 7 months after the peak of maternal ZIKV infection. The highest estimated incidence of maternal ZIKV infections and microcephaly were 39.3 and 2.5 cases per 1000 livebirths, respectively. Districts with better socioeconomic indicators and with higher proportions of self-identified white inhabitants were associated with lower risks of maternal ZIKV infection. Overall, the findings indicate heterogeneity in the spatiotemporal patterns of maternal ZIKV infections and microcephaly, which were correlated with seasonality and included a high-risk geographic cluster. Our findings identified geographically and socio-economically underprivileged groups that would benefit from targeted interventions to reduce exposure to vector-borne infections.

The first wave of Zika virus (ZIKV) epidemic and its Congenital Zika Syndrome, has vanished. However, the consequences have remained for the affected children and families ever since.

In Brazil, the first cases of microcephaly, detected in the end of 2015 in the Northeast region, especially in coastal cities, quickly spread to other regions and cities in countryside of Brazil. Understanding the temporal and spatial dynamics of cases distribution is essential to identify areas of greater risk and enable preparedness for a future wave of cases.

In this study, we analyzed the spatiotemporal distribution of cases of ZIKV infection in pregnant women and cases of microcephaly in newborns by district, over a five-year period, in a large city in Midwest Brazil. Additionally, cases of microcephaly were correlated with the socioeconomic and structural conditions at the local level.

Our findings indicate heterogeneity in the spatiotemporal patterns of maternal ZIKV infections and microcephaly, which were correlated with seasonality and included a persistent high-risk geographic location (cluster) in the city of Goiania. We could identify geographically and socio-economically underprivileged groups, with higher risk for ZIKV infection, that would benefit from targeted interventions to reduce exposure to new vector borne infections.

Real-time estimation of the epidemic reproduction number: Scoping review of the applications and challenges

The time-varying reproduction number (Rt) is an important measure of transmissibility during outbreaks. Estimating whether and how rapidly an outbreak is growing (Rt > 1) or declining (Rt < 1) can inform the design, monitoring and adjustment of control measures in real-time. We use a popular R package for Rt estimation, EpiEstim, as a case study to evaluate the contexts in which Rt estimation methods have been used and identify unmet needs which would enable broader applicability of these methods in real-time. A scoping review, complemented by a small EpiEstim user survey, highlight issues with the current approaches, including the quality of input incidence data, the inability to account for geographical factors, and other methodological issues. We summarise the methods and software developed to tackle the problems identified, but conclude that significant gaps remain which should be addressed to enable easier, more robust and applicable estimation of Rt during epidemics.

Intranasal Immunization with Zika Virus Envelope Domain III-Flagellin Fusion Protein Elicits Systemic and Mucosal Immune Responses and Protection against Subcutaneous and Intravaginal Virus Challenges

Zika virus (ZIKV) infections in humans are mainly transmitted by the mosquito vectors, but human-to-human sexual transmission is also another important route. Developing a ZIKV mucosal vaccine that can elicit both systemic and mucosal immune responses is of particular interest. In this study, we constructed a recombinant ZIKV envelope DIII (ZDIII) protein genetically fused with Salmonella typhimurium flagellin (FliC-ZDIII) as a novel mucosal antigen for intranasal immunization. The results indicated that the FliC-ZDIII fusion proteins formulated with E. coli heat-labile enterotoxin B subunit (LTIIb-B5) adjuvant greatly increased the ZDIII-specific IgG, IgA, and neutralizing titers in sera, and the ZDIII-specific IgA titers in bronchoalveolar lavage and vaginal fluids. Protective immunity was further assessed by subcutaneous and intravaginal ZIKV challenges. The second-generation FliCΔD3-2ZDIII was shown to result in a reduced titer of anti-FliC IgG antibodies in sera and still retained the same levels of serum IgG, IgA, and neutralizing antibodies and mucosal IgA antibodies without compromising the vaccine antigenicity. Therefore, intranasal immunization with FliCΔD3-2ZDIII fusion proteins formulated with LTIIb-B5 adjuvant elicited the greatest protective immunity against subcutaneous and intravaginal ZIKV challenges. Our findings indicated that the combination of FliCΔD3-2ZDIII fusion proteins and LTIIb-B5 adjuvant for intranasal immunization can be used for developing ZIKV mucosal vaccines.

The costs and benefits of primary prevention of zoonotic pandemics

The lives lost and economic costs of viral zoonotic pandemics have steadily increased over the past century. Prominent policymakers have promoted plans that argue the best ways to address future pandemic catastrophes should entail, "detecting and containing emerging zoonotic threats." In other words, we should take actions only after humans get sick. We sharply disagree. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We compute the annualized damages from emerging viral zoonoses. We explore three practical actions to minimize the impact of future pandemics: better surveillance of pathogen spillover and development of global databases of virus genomics and serology, better management of wildlife trade, and substantial reduction of deforestation. We find that these primary pandemic prevention actions cost less than 1/20th the value of lives lost each year to emerging viral zoonoses and have substantial cobenefits.

Game-Theoretical Model of the Voluntary Use of Insect Repellents to Prevent Zika Fever

Zika fever is an emerging mosquito-borne disease. While it often causes no or only mild symptoms that are similar to dengue fever, Zika virus can spread from a pregnant woman to her baby and cause severe birth defects. There is no specific treatment or vaccine, but the disease can be mitigated by using several control strategies, generally focusing on the reduction in mosquitoes or mosquito bites. In this paper, we model Zika virus transmission and incorporate a game-theoretical approach to study a repeated population game of DEET usage to prevent insect bites. We show that the optimal use effectively leads to disease elimination. This result is robust and not significantly dependent on the cost of the insect repellents.

The Impact of Deforestation, Urbanization, and Changing Land Use Patterns on the Ecology of Mosquito and Tick-Borne Diseases in Central America

Central America is a unique geographical region that connects North and South America, enclosed by the Caribbean Sea to the East, and the Pacific Ocean to the West. This region, encompassing Belize, Costa Rica, Guatemala, El Salvador, Honduras, Panama, and Nicaragua, is highly vulnerable to the emergence or resurgence of mosquito-borne and tick-borne diseases due to a combination of key ecological and socioeconomic determinants acting together, often in a synergistic fashion. Of particular interest are the effects of land use changes, such as deforestation-driven urbanization and forest degradation, on the incidence and prevalence of these diseases, which are not well understood. In recent years, parts of Central America have experienced social and economic improvements; however, the region still faces major challenges in developing effective strategies and significant investments in public health infrastructure to prevent and control these diseases. In this article, we review the current knowledge and potential impacts of deforestation, urbanization, and other land use changes on mosquito-borne and tick-borne disease transmission in Central America and how these anthropogenic drivers could affect the risk for disease emergence and resurgence in the region. These issues are addressed in the context of other interconnected environmental and social challenges.

Microbial Composition in Larval Water Enhances Aedes aegypti Development but Reduces Transmissibility of Zika Virus

Arthropod-borne viruses comprise a significant global disease burden. Surveillance and mitigation of arboviruses like Zika virus (ZIKV) require accurate estimates of transmissibility by vector mosquitoes. Although Aedes species mosquitoes are established as competent ZIKV vectors, differences in experimental protocols across studies prevent direct comparisons of relative transmissibility. An understudied factor complicating these comparisons is differential environmental microbiota exposures, where most vector competence studies use mosquitoes reared in laboratory tap water, which does not represent the microbial complexity of environmental water where wild larvae develop. We simulated natural larval development by rearing Californian Aedes aegypti larvae with microbes obtained from cemetery headstone water compared to conventional tap water. A. aegypti larvae reared in environmental cemetery water pupated 3 days faster and at higher rates. Mosquitoes reared in environmental water were less competent vectors of ZIKV than laboratory water-reared A. aegypti, as evidenced by significantly reduced infection and transmission rates. Microbiome comparisons of laboratory water- and environment water-reared mosquitoes and their rearing water showed significantly higher bacterial diversity in environment water. Despite this pattern, corresponding differences in bacterial diversity were not consistently observed between the respective adult mosquitoes. We also observed that the microbial compositions of adult mosquitoes differed more by whether they ingested a bloodmeal than by larval water type. Together, these results highlight the role of transient microbes in the larval environment in modulating A. aegypti vector competence for ZIKV. Laboratory vector competence likely overestimates the true transmissibility of arboviruses like ZIKV when conventional laboratory water is used for rearing. IMPORTANCE We observed that A. aegypti mosquitoes reared in water from cemetery headstones instead of the laboratory tap exhibited a reduced capacity to become infected with and transmit Zika virus. Water from the environment contained more bacterial species than tap water, but these bacteria were not consistently detected in adult mosquitoes. Our results suggest that rearing mosquito larvae in water collected from local environments as opposed to laboratory tap water, as is conventional, could provide a more realistic assessment of ZIKV vector competence since it better recapitulates the natural environment in which larvae develop. Given that laboratory vector competence is used to define the species to target for control, the use of environmental water to rear larvae could better approximate the microbial exposures of wild mosquitoes, lessening the potential for overestimating ZIKV transmission risk. These studies raise the question of whether rearing larvae in natural water sources also reduces vector competence for other mosquito-borne viruses.

Viral proteases: Structure, mechanism and inhibition

Viral proteases are diverse in structure, oligomeric state, catalytic mechanism, and substrate specificity. This chapter focuses on proteases from viruses that are relevant to human health: human immunodeficiency virus subtype 1 (HIV-1), hepatitis C (HCV), human T-cell leukemia virus type 1 (HTLV-1), flaviviruses, enteroviruses, and coronaviruses. The proteases of HIV-1 and HCV have been successfully targeted for therapeutics, with picomolar FDA-approved drugs currently used in the clinic. The proteases of HTLV-1 and the other virus families remain emerging therapeutic targets at different stages of the drug development process. This chapter provides an overview of the current knowledge on viral protease structure, mechanism, substrate recognition, and inhibition. Particular focus is placed on recent advances in understanding the molecular basis of diverse substrate recognition and resistance, which is essential toward designing novel protease inhibitors as antivirals.

The seasonal behaviour of COVID-19 and its galectin-like culprit of the viral spike

Seasonal behaviour is an attribute of many viral diseases. Like other 'winter' RNA viruses, infections caused by the causative agent of COVID-19, SARS-CoV-2, appear to exhibit significant seasonal changes. Here we discuss the seasonal behaviour of COVID-19, emerging viral phenotypes, viral evolution, and how the mutational landscape of the virus affects the seasonal attributes of the disease. We propose that the multiple seasonal drivers behind infectious disease spread (and the spread of COVID-19 specifically) are in 'trade-off' relationships and can be better described within a framework of a 'triangle of viral persistence' modulated by the environment, physiology, and behaviour. This 'trade-off' exists as one trait cannot increase without a decrease in another. We also propose that molecular components of the virus can act as sensors of environment and physiology, and could represent molecular culprits of seasonality. We searched for flexible protein structures capable of being modulated by the environment and identified a galectin-like fold within the N-terminal domain of the spike protein of SARS-CoV-2 as a potential candidate. Tracking the prevalence of mutations in this structure resulted in the identification of a hemisphere-dependent seasonal pattern driven by mutational bursts. We propose that the galectin-like structure is a frequent target of mutations because it helps the virus evade or modulate the physiological responses of the host to further its spread and survival. The flexible regions of the N-terminal domain should now become a focus for mitigation through vaccines and therapeutics and for prediction and informed public health decision making.

Zika virus infection and microcephaly: spatial analysis and socio-environmental determinants in a region of high Aedes aegypti infestation in the Central-West Region of Brazil

Background

More than 5 years after the Zika virus (ZIKV) epidemic, Zika infection remains a major concern in regions with high Aedes infestation. The objectives of this study were (i) to identify clusters of ZIKV infection and microcephaly, and/or central nervous system (CNS) alterations associated with congenital infection during the epidemic peak in 2016 and subsequently, in 2017 and 2018; (ii) to measure the non-spatial correlation between ZIKV infection and microcephaly and/or CNS alterations associated with congenital infection; and (iii) to analyse the sociodemographic/economic, health, and environmental determinants associated with the incidence of ZIKV in a region of high infestation by Aedes aegypti in the Central-West Region of Brazil.

Methods

This ecological study analysed 246 municipalities in the state of Goiás (6.9 million inhabitants). The data were obtained from the Information System for Notifiable Diseases (ZIKV cases) and the Public Health Event Registry (microcephaly and/or CNS alterations associated with congenital infection). Incidence rates and prevalence of ZIKA infection were smoothed by an empirical Bayesian estimator (LEbayes), producing the local empirical Bayesian rate (LEBR). In the spatial analysis, ZIKV infection and microcephaly cases were georeferenced by the municipality of residence for 2016 and grouped for 2017 and 2018. Global Moran's I and the Hot Spot Analysis tool (Getis-Ord Gi* statistics) were used to analyse the spatial autocorrelation and clusters of ZIKV infection and microcephaly, respectively. A generalised linear model from the Poisson family was used to assess the association between ecological determinants and the smoothing incidence rate of ZIKV infection.

Results

A total of 9892 cases of acute ZIKV infection and 121 cases of microcephaly were confirmed. The mean LEBR of the ZIKV infection in the 246 municipalities was 22.3 cases/100,000 inhabitants in 2016, and 10.3 cases/100,000 inhabitants in 2017 and 2018. The LEBR of the prevalence rate of microcephaly and/or CNS alterations associated with congenital infection was 7 cases/10,000 live births in 2016 and 2 cases/10,000 live births during 2017–2018. Hotspots of ZIKV infection and microcephaly cases were identified in the capital and neighbouring municipalities in 2016, with new clusters in the following years. In a multiple regression Poisson analysis, ZIKV infection was associated with higher population density, the incidence of dengue, Aedes larvae infestation index, and average rainfall. The important determinant of ZIKV infection incidence reduction was the increase in households attended by endemic disease control agents.

Conclusions

Our analyses were able to capture, in a more granular way, aspects that make it possible to inform public managers of the sentinel areas identified in the post-epidemic hotspots.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06805-1.

Anti-flavivirus Properties of Lipid-Lowering Drugs

Although Flaviviruses such as dengue (DENV) and zika (ZIKV) virus are important human pathogens, an effective vaccine or antiviral treatment against them is not available. Hence, the search for new strategies to control flavivirus infections is essential. Several studies have shown that the host lipid metabolism could be an antiviral target because cholesterol and other lipids are required during the replicative cycle of different Flaviviridae family members. FDA-approved drugs with hypolipidemic effects could be an alternative for treating flavivirus infections. However, a better understanding of the regulation between host lipid metabolism and signaling pathways triggered during these infections is required. The metabolic pathways related to lipid metabolism modified during DENV and ZIKV infection are analyzed in this review. Additionally, the role of lipid-lowering drugs as safe host-targeted antivirals is discussed.

NS2B-NS3 protease inhibitors as promising compounds in the development of antivirals against Zika virus: A systematic review

Zika virus (ZIKV) infections are associated with severe neurological complications and are a global public health concern. There are no approved vaccines or antiviral drugs to inhibit ZIKV replication. NS2B-NS3 protease (NS2B-NS3 pro), which is essential for viral replication, is a promising molecular target for anti-ZIKV drugs. We conducted a systematic review to identify compounds with promising effects against ZIKV; we discussed their pharmacodynamic and pharmacophoric characteristics. The online search, performed using the PubMed/MEDLINE and SCOPUS databases, yielded 56 articles; seven relevant studies that reported nine promising compounds with inhibitory activity against ZIKV NS2B-NS3 pro were selected. Of these, five (niclosamide, nitazoxanide, bromocriptine, temoporfin, and novobiocin) are currently available on the market and have been tested for off-label use against ZIKV. The 50% inhibitory concentration values of these compounds for the inhibition of NS2B-NS3 pro ranged at 0.38-21.6 µM; most compounds exhibited noncompetitive inhibition (66%). All compounds that could inhibit the NS2B-NS3 pro complex showed potent in vitro anti-ZIKV activity with a 50% effective concentration ranging 0.024-50 µM. The 50% cytotoxic concentration of the compounds assayed using A549, Vero, and WRL-69 cell lines ranged at 0.6-1388.02 µM and the selectivity index was 3.07-1698. This review summarizes the most promising antiviral agents against ZIKV that have inhibitory activity against viral proteases.

Nanoscience and quantum science-led biocidal and antiviral strategies

The severe acute respiratory syndrome coronavirus (SARS-CoV-2) caused the COVID-19 pandemic. According to the World Health Organization, this pandemic continues to be a serious threat to public health due to the worldwide spread of variants and their higher rate of transmissibility. A range of measures are necessary to slow the pandemic and save lives, which include constant evaluation and the careful adjustment of public-health responses augmented by medical treatments, vaccines and protective gear. It is hypothesized that nanostructured particulates underpinned by nanoscience and quantum science yield high-performing antiviral strategies, which can be applied in preventive, diagnostic, and therapeutic applications such as face masks, respirators, COVID test kits, vaccines, and drugs. This review is aimed at providing comprehensive and cohesive perspectives on various nanostructures that are suited to intensifying and amplifying the effectiveness of antiviral strategies. Growing scientific literature over the past eighteen months indicates that quantum dots, iron oxide, silicon oxide, polymeric and metallic nanoparticles have been employed in COVID-19 diagnostic assays, vaccines, and personal protective equipment (PPE). Quantum dots have displayed their suitability as more sensitive imaging probes in diagnostics and prognostics, and as controlled drug-release carriers that target the virus. Nanoscience and quantum science have assisted the design of advanced vaccine delivery since nanostructured materials are suited for antigen delivery, as mimics of viral structures and as adjuvants. Furthermore, the quantum science- and nanoscience-supported tailored functionalization of nanostructured materials offers insight and pathways to deal with future pandemics. This review seeks to illustrate several examples, and to explain the underpinning quantum science and nanoscience phenomena, which include wave functions, electrostatic interactions, van der Waals forces, thermal and electrodynamic fluctuations, dispersion forces, local field-enhancement effects, and the generation of reactive oxygen species (ROS). This review discusses how nanostructured materials are helpful in the detection, prevention, and treatment of the SARS-CoV-2 infection, other known viral infection diseases, and future pandemics.

Spatial and temporal invasion dynamics of the 2014-2017 Zika and chikungunya epidemics in Colombia

Zika virus (ZIKV) and chikungunya virus (CHIKV) were recently introduced into the Americas resulting in significant disease burdens. Understanding their spatial and temporal dynamics at the subnational level is key to informing surveillance and preparedness for future epidemics. We analyzed anonymized line list data on approximately 105,000 Zika virus disease and 412,000 chikungunya fever suspected and laboratory-confirmed cases during the 2014–2017 epidemics. We first determined the week of invasion in each city. Out of 1,122, 288 cities met criteria for epidemic invasion by ZIKV and 338 cities by CHIKV. We analyzed risk factors for invasion using linear and logistic regression models. We also estimated that the geographic origin of both epidemics was located in Barranquilla, north Colombia. We assessed the spatial and temporal invasion dynamics of both viruses to analyze transmission between cities using a suite of (i) gravity models, (ii) Stouffer’s rank models, and (iii) radiation models with two types of distance metrics, geographic distance and travel time between cities. Invasion risk was best captured by a gravity model when accounting for geographic distance and intermediate levels of density dependence; Stouffer’s rank model with geographic distance performed similarly well. Although a few long-distance invasion events occurred at the beginning of the epidemics, an estimated distance power of 1.7 (95% CrI: 1.5–2.0) from the gravity models suggests that spatial spread was primarily driven by short-distance transmission. Similarities between the epidemics were highlighted by jointly fitted models, which were preferred over individual models when the transmission intensity was allowed to vary across arboviruses. However, ZIKV spread considerably faster than CHIKV.

Understanding the spread of infectious diseases across space and time is critical for preparedness, designing interventions, and elucidating mechanisms underlying transmission. We analyzed human case data from over 500,000 reported cases to investigate the spread of the recent Zika virus (ZIKV) and chikungunya virus (CHIKV) epidemics in Colombia. Both viruses were introduced into northern Colombia. We found that gravity models and Stouffer’s rank models best described transmission and that transmission mainly occurred over short distances. Our results highlight similarities and key differences between the ZIKV and CHIKV epidemics in Colombia, which can be used to anticipate future epidemic waves and prioritize cities for active surveillance and targeted interventions.

A Comparative Analysis of Statistical Methods to Estimate the Reproduction Number in Emerging Epidemics, With Implications for the Current Coronavirus Disease 2019 (COVID-19) Pandemic

BACKGROUND

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues its rapid global spread, quantification of local transmission patterns has been, and will continue to be, critical for guiding the pandemic response. Understanding the accuracy and limitations of statistical methods to estimate the basic reproduction number, R0, in the context of emerging epidemics is therefore vital to ensure appropriate interpretation of results and the subsequent implications for control efforts.

METHODS

Using simulated epidemic data, we assess the performance of 7 commonly used statistical methods to estimate R0 as they would be applied in a real-time outbreak analysis scenario: fitting to an increasing number of data points over time and with varying levels of random noise in the data. Method comparison was also conducted on empirical outbreak data, using Zika surveillance data from the 2015-2016 epidemic in Latin America and the Caribbean.

RESULTS

We find that most methods considered here frequently overestimate R0 in the early stages of epidemic growth on simulated data, the magnitude of which decreases when fitted to an increasing number of time points. This trend of decreasing bias over time can easily lead to incorrect conclusions about the course of the epidemic or the need for control efforts.

CONCLUSIONS

We show that true changes in pathogen transmissibility can be difficult to disentangle from changes in methodological accuracy and precision in the early stages of epidemic growth, particularly for data with significant over-dispersion. As localized epidemics of SARS-CoV-2 take hold around the globe, awareness of this trend will be important for appropriately cautious interpretation of results and subsequent guidance for control efforts.

The epidemiology of Mayaro virus in the Americas: A systematic review and key parameter estimates for outbreak modelling

Mayaro virus (MAYV) is an arbovirus that is endemic to tropical forests in Central and South America, particularly within the Amazon basin. In recent years, concern has increased regarding MAYV's ability to invade urban areas and cause epidemics across the region. We conducted a systematic literature review to characterise the evolutionary history of MAYV, its transmission potential, and exposure patterns to the virus. We analysed data from the literature on MAYV infection to produce estimates of key epidemiological parameters, including the generation time and the basic reproduction number, R0. We also estimated the force-of-infection (FOI) in epidemic and endemic settings. Seventy-six publications met our inclusion criteria. Evidence of MAYV infection in humans, animals, or vectors was reported in 14 Latin American countries. Nine countries reported evidence of acute infection in humans confirmed by viral isolation or reverse transcription-PCR (RT-PCR). We identified at least five MAYV outbreaks. Seroprevalence from population based cross-sectional studies ranged from 21% to 72%. The estimated mean generation time of MAYV was 15.2 days (95% CrI: 11.7-19.8) with a standard deviation of 6.3 days (95% CrI: 4.2-9.5). The per-capita risk of MAYV infection (FOI) ranged between 0.01 and 0.05 per year. The mean R0 estimates ranged between 2.1 and 2.9 in the Amazon basin areas and between 1.1 and 1.3 in the regions outside of the Amazon basin. Although MAYV has been identified in urban vectors, there is not yet evidence of sustained urban transmission. MAYV's enzootic cycle could become established in forested areas within cities similar to yellow fever virus.

The long-term changing dynamics of dengue infectivity in Guangdong, China, from 2008-2018: a modelling analysis

BACKGROUND

Dengue remains a severe threat to public health in tropical and subtropical regions. In China, over 85% of domestic dengue cases are in the Guangdong province and there were 53 139 reported cases during 2008-2018. In Guangdong, the 2014 dengue outbreak was the largest in the last 20 y and it was probably triggered by a new strain imported from other regions.

METHODS

We studied the long-term patterns of dengue infectivity in Guangdong from 2008-2018 and compared the infectivity estimates across different periods.

RESULTS

We found that the annual epidemics approximately followed exponential growth during 2011-2014. The transmission rates were at a low level during 2008-2012, significantly increased 1.43-fold [1.22, 1.69] during 2013-2014 and then decreased back to a low level after 2015. By using the mosquito index and the likelihood-inference approach, we found that the new strain most likely invaded Guangdong in April 2014.

CONCLUSIONS

The long-term changing dynamics of dengue infectivity are associated with the new dengue virus strain invasion and public health control programmes. The increase in infectiousness indicates the potential for dengue to go from being imported to becoming an endemic in Guangdong, China.

Transient disease dynamics across ecological scales

Analyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12080-021-00514-w.

The epidemicity index of recurrent SARS-CoV-2 infections

Several indices can predict the long-term fate of emerging infectious diseases and the effect of their containment measures, including a variety of reproduction numbers (e.g. [Formula: see text]). Other indices evaluate the potential for transient increases of epidemics eventually doomed to disappearance, based on generalized reactivity analysis. They identify conditions for perturbations to a stable disease-free equilibrium ([Formula: see text]) to grow, possibly causing significant damage. Here, we introduce the epidemicity index e0, a threshold-type indicator: if e0 > 0, initial foci may cause infection peaks even if [Formula: see text]. Therefore, effective containment measures should achieve a negative epidemicity index. We use spatially explicit models to rank containment measures for projected evolutions of the ongoing pandemic in Italy. There, we show that, while the effective reproduction number was below one for a sizable timespan, epidemicity remained positive, allowing recurrent infection flare-ups well before the major epidemic rebounding observed in the fall.

Effects of changes in temperature on Zika dynamics and control

When a rare pathogen emerges to cause a pandemic, it is critical to understand its dynamics and the impact of mitigation measures. We use experimental data to parametrize a temperature-dependent model of Zika virus (ZIKV) transmission dynamics and analyse the effects of temperature variability and control-related parameters on the basic reproduction number (R0) and the final epidemic size of ZIKV. Sensitivity analyses show that these two metrics are largely driven by different parameters, with the exception of temperature, which is the dominant driver of epidemic dynamics in the models. Our R0 estimate has a single optimum temperature (≈30°C), comparable to other published results (≈29°C). However, the final epidemic size is maximized across a wider temperature range, from 24 to 36°C. The models indicate that ZIKV is highly sensitive to seasonal temperature variation. For example, although the model predicts that ZIKV transmission cannot occur at a constant temperature below 23°C (≈ average annual temperature of Rio de Janeiro, Brazil), the model predicts substantial epidemics for areas with a mean temperature of 20°C if there is seasonal variation of 10°C (≈ average annual temperature of Tampa, Florida). This suggests that the geographical range of ZIKV is wider than indicated from static R0 models, underscoring the importance of climate dynamics and variation in the context of broader climate change on emerging infectious diseases.

The antiviral effect of metformin on zika and dengue virus infection

The Dengue (DENV) and zika (ZIKV) virus infections are currently a public health concern. At present, there is no treatment or a safe and effective vaccine for these viruses. Hence, the development of new strategies as host-directed therapy is required. In this sense, Metformin (MET), an FDA-approved drug used for the treatment of type 2 diabetes, has shown an anti-DENV effect in vitro by activating AMPK and reducing HMGCR activity. In this study, MET treatment was evaluated during in vitro and in vivo ZIKV infection and compared to MET treatment during DENV infection. Our results demonstrated that MET has a broad in vitro antiviral spectrum. MET inhibited ZIKV infection in different cell lines, but it was most effective in inhibiting DENV and yellow fever virus (YFV) infection in Huh-7 cells. However, the drug failed to protect against ZIKV infection when AG129 immunodeficient mice were used as in vivo model. Interestingly, MET increased DENV-infected male mice's survival time, reducing the severe signs of the disease. Together, these findings indicate that, although MET was an effective antiviral agent to inhibit in vitro and in vivo DENV infection, it could only inhibit in vitro ZIKV infection.

Statistical Estimation of the Reproductive Number From Case Notification Data

The reproductive number, or reproduction number, is a valuable metric in understanding infectious disease dynamics. There is a large body of literature related to its use and estimation. In the last 15 years, there has been tremendous progress in statistically estimating this number using case notification data. These approaches are appealing because they are relevant in an ongoing outbreak (e.g., for assessing the effectiveness of interventions) and do not require substantial modeling expertise to be implemented. In this article, we describe these methods and the extensions that have been developed. We provide insight into the distinct interpretations of the estimators proposed and provide real data examples to illustrate how they are implemented. Finally, we conclude with a discussion of available software and opportunities for future development.

Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016

Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barré Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of August 15, 2016 (the 33^rd week of year), and 120 to 140 (50% credible interval [CrI], 95% CrI: 97 to 170) weekly infections per 10,000 population occurred at the peak. By the end of 2016, we estimated that approximately 890,000 (95% CrI: 660,000 to 1,100,000) individuals were infected in 2016 (26%, 95% CrI: 19% to 33%, of the population infected). Utilizing multiple indicators offers the opportunity for real-time and retrospective situational awareness to support epidemic preparedness and response.

Zika virus (ZIKV) infections, like many infections, are generally underreported due to asymptomatic, mild, or unrecognized cases. Using available surveillance indicators reflecting imperfect proxies of infection, we developed a modeling approach to estimate the weekly incidence of infection by combining independent surveillance indicators and assumptions about system-specific reporting biases in a Bayesian framework. Using our approach, we estimated that approximately 890,000 people in the population were infected with Zika in Puerto Rico in 2016, much higher than the 36,316 reported confirmed infections. Our framework has broad application to other diseases where cases may be underreported through traditional disease surveillance and can provide near real-time changes in incidences.

Interactions between timing and transmissibility explain diverse flavivirus dynamics in Fiji

Zika virus (ZIKV) has caused large, brief outbreaks in isolated populations, however ZIKV can also persist at low levels over multiple years. The reasons for these diverse transmission dynamics remain poorly understood. In Fiji, which has experienced multiple large single-season dengue epidemics, there was evidence of multi-year transmission of ZIKV between 2013 and 2017. To identify factors that could explain these differences in dynamics between closely related mosquito-borne flaviviruses, we jointly fit a transmission dynamic model to surveillance, serological and molecular data. We estimate that the observed dynamics of ZIKV were the result of two key factors: strong seasonal effects, which created an ecologically optimal time of year for outbreaks; and introduction of ZIKV after this optimal time, which allowed ZIKV transmission to persist over multiple seasons. The ability to jointly fit to multiple data sources could help identify a similar range of possible outbreak dynamics in other settings.

Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations

For endemic pathogens, seroprevalence mimics overall exposure and is minimally influenced by the time that recent infections take to seroconvert. Simulating spatially-explicit and stochastic outbreaks, we set out to explore how, for emerging pathogens, the mix of exponential growth in infection events and a constant rate for seroconversion events could lead to real-time significant differences in the total numbers of exposed versus seropositive. We find that real-time seroprevalence of an emerging pathogen can underestimate exposure depending on measurement time, epidemic doubling time, duration and natural variation in the time to seroconversion among hosts. We formalise mathematically how underestimation increases non-linearly as the host's time to seroconversion is ever longer than the pathogen's doubling time, and how more variable time to seroconversion among hosts results in lower underestimation. In practice, assuming that real-time seroprevalence reflects the true exposure to emerging pathogens risks overestimating measures of public health importance (e.g. infection fatality ratio) as well as the epidemic size of future waves. These results contribute to a better understanding and interpretation of real-time serological data collected during the emergence of pathogens in infection-naive host populations.

Structure-Based Virtual Screening: Identification of a Novel NS2B-NS3 Protease Inhibitor with Potent Antiviral Activity against Zika and Dengue Viruses

Zika virus (ZIKV), which is associated with severe diseases in humans, has spread rapidly and globally since its emergence. ZIKV and dengue virus (DENV) are closely related, and antibody-dependent enhancement (ADE) of infection between cocirculating ZIKV and DENV may exacerbate disease. Despite these serious threats, there are currently no approved antiviral drugs against ZIKV and DENV. The NS2B-NS3 viral protease is an attractive antiviral target because it plays a pivotal role in polyprotein cleavage, which is required for viral replication. Thus, we sought to identify novel inhibitors of the NS2B-NS3 protease. To that aim, we performed structure-based virtual screening using 467,000 structurally diverse chemical compounds. Then, a fluorescence-based protease inhibition assay was used to test whether the selected candidates inhibited ZIKV protease activity. Among the 123 candidate inhibitors selected from virtual screening, compound 1 significantly inhibited ZIKV NS2B-NS3 protease activity in vitro. In addition, compound 1 effectively inhibited ZIKV and DENV infection of human cells. Molecular docking analysis suggested that compound 1 binds to the NS2B-NS3 protease of ZIKV and DENV. Thus, compound 1 could be used as a new therapeutic option for the development of more potent antiviral drugs against both ZIKV and DENV, reducing the risks of ADE.

The value of infectious disease modeling and trend assessment: a public health perspective

INTRODUCTION

Disease outbreaks of acquired immunodeficiency syndrome, severe acute respiratory syndrome, pandemic H1N1, H7N9, H5N1, Ebola, Zika, Middle East respiratory syndrome, and recently COVID-19 have raised the attention of the public over the past half-century. Revealing the characteristics and epidemic trends are important parts of disease control. The biological scenarios including transmission characteristics can be constructed and translated into mathematical models, which can help to predict and gain a deeper understanding of diseases.

AREAS COVERED

This review discusses the models for infectious diseases and highlights their values in the field of public health. This information will be of interest to mathematicians and clinicians, and make a significant contribution toward the development of more specific and effective models. Literature searches were performed using the online database of PubMed (inception to August 2020).

EXPERT OPINION

Modeling could contribute to infectious disease control by means of predicting the scales of disease epidemics, indicating the characteristics of disease transmission, evaluating the effectiveness of interventions or policies, and warning or forecasting during the pre-outbreak of diseases. With the development of theories and the ability of calculations, infectious disease modeling would play a much more important role in disease prevention and control of public health.

Zika virus envelope nanoparticle antibodies protect mice without risk of disease enhancement

Background

Zika virus (ZIKV), an arbovirus capable of causing neurological abnormalities, is a recognised human pathogen, for which a vaccine is required. As ZIKV antibodies can mediate antibody-dependent enhancement (ADE) of dengue virus (DENV) infection, a ZIKV vaccine must not only protect against ZIKV but must also not sensitise vaccinees to severe dengue.

Methods

The N-terminal 80% of ZIKV envelope protein (80E) was expressed in Pichia pastoris and its capacity to self-assemble into particulate structures evaluated using dynamic light scattering and electron microscopy. Antigenic integrity of the 80E protein was evaluated using ZIKV-specific monoclonal antibodies. Its immunogenicity and protective efficacy were assessed in BALB/c and C57BL/6 Stat2^−/− mice, respectively. Its capacity to enhance DENV and ZIKV infection was assessed in AG129 and C57BL/6 Stat2^−/− mice, respectively.

Findings

ZIKV-80E protein self-assembled into discrete nanoparticles (NPs), which preserved the antigenic integrity of neutralising epitopes on E domain III (EDIII) and elicited potent ZIKV-neutralising antibodies predominantly against this domain in BALB/c mice. These antibodies conferred statistically significant protection in vivo (p = 0.01, Mantel–Cox test), and did not exacerbate sub-lethal DENV-2 or ZIKV challenges in vivo.

Interpretation

Yeast-expressed ZIKV-80E, which forms highly immunogenic EDIII-displaying NPs, elicits ZIKV EDIII-specific antibodies capable of offering significant protection in vivo, without the potential risk of ADE upon subsequent DENV-2 or ZIKV infection. This offers a promising vaccine candidate for further development.

Funding

This study was supported partly by ICGEB, India, and by NIAID, USA.