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Elliott KC, Mattapallil JJ. Zika Virus-A Reemerging Neurotropic Arbovirus Associated with Adverse Pregnancy Outcomes and Neuropathogenesis. Pathogens 2024; 13:177. [PMID: 38392915 PMCID: PMC10892292 DOI: 10.3390/pathogens13020177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Revised: 02/07/2024] [Accepted: 02/11/2024] [Indexed: 02/25/2024] Open
Abstract
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.
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Affiliation(s)
- Kenneth C. Elliott
- Department of Microbiology & Immunology, The Henry M Jackson Foundation for Military Medicine, Uniformed Services University, Bethesda, MD 20814, USA
- Department of Microbiology & Immunology, Uniformed Services University, Bethesda, MD 20814, USA
| | - Joseph J. Mattapallil
- Department of Microbiology & Immunology, Uniformed Services University, Bethesda, MD 20814, USA
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2
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McMahon DE, Schuetz AN, Kovarik CL. Emerging infectious diseases of the skin: a review of clinical and histologic findings. Hum Pathol 2023; 140:196-213. [PMID: 37454994 DOI: 10.1016/j.humpath.2023.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 06/29/2023] [Accepted: 07/05/2023] [Indexed: 07/18/2023]
Abstract
Emerging infectious diseases are of great importance to public health and clinical practice. This review aims to characterize the clinical and histopathologic features of emerging infectious diseases with cutaneous manifestations in order to increase awareness of these entities among dermatologists, pathologists, and dermatopathologists.
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Affiliation(s)
- Devon E McMahon
- Department of Dermatology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Audrey N Schuetz
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Carrie L Kovarik
- Department of Dermatology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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3
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Van Wyk H, Eisenberg JNS, Brouwer AF. Long-term projections of the impacts of warming temperatures on Zika and dengue risk in four Brazilian cities using a temperature-dependent basic reproduction number. PLoS Negl Trop Dis 2023; 17:e0010839. [PMID: 37104296 PMCID: PMC10138270 DOI: 10.1371/journal.pntd.0010839] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 03/21/2023] [Indexed: 04/28/2023] Open
Abstract
For vector-borne diseases the basic reproduction number [Formula: see text], a measure of a disease's epidemic potential, is highly temperature-dependent. Recent work characterizing these temperature dependencies has highlighted how climate change may impact geographic disease spread. We extend this prior work by examining how newly emerging diseases, like Zika, will be impacted by specific future climate change scenarios in four diverse regions of Brazil, a country that has been profoundly impacted by Zika. We estimated a [Formula: see text], derived from a compartmental transmission model, characterizing Zika (and, for comparison, dengue) transmission potential as a function of temperature-dependent biological parameters specific to Aedes aegypti. We obtained historical temperature data for the five-year period 2015-2019 and projections for 2045-2049 by fitting cubic spline interpolations to data from simulated atmospheric data provided by the CMIP-6 project (specifically, generated by the GFDL-ESM4 model), which provides projections under four Shared Socioeconomic Pathways (SSP). These four SSP scenarios correspond to varying levels of climate change severity. We applied this approach to four Brazilian cities (Manaus, Recife, Rio de Janeiro, and São Paulo) that represent diverse climatic regions. Our model predicts that the [Formula: see text] for Zika peaks at 2.7 around 30°C, while for dengue it peaks at 6.8 around 31°C. We find that the epidemic potential of Zika will increase beyond current levels in Brazil in all of the climate scenarios. For Manaus, we predict that the annual [Formula: see text] range will increase from 2.1-2.5, to 2.3-2.7, for Recife we project an increase from 0.4-1.9 to 0.6-2.3, for Rio de Janeiro from 0-1.9 to 0-2.3, and for São Paulo from 0-0.3 to 0-0.7. As Zika immunity wanes and temperatures increase, there will be increasing epidemic potential and longer transmission seasons, especially in regions where transmission is currently marginal. Surveillance systems should be implemented and sustained for early detection.
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Affiliation(s)
- Hannah Van Wyk
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Joseph N. S. Eisenberg
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Andrew F. Brouwer
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
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4
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López L, Dommar C, San José A, Meyers L, Fox S, Castro L, Rodó X. Changing risk of arboviral emergence in Catalonia due to higher probability of autochthonous outbreaks. Ecol Modell 2023. [DOI: 10.1016/j.ecolmodel.2022.110258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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Aryaprema VS, Steck MR, Peper ST, Xue RD, Qualls WA. A systematic review of published literature on mosquito control action thresholds across the world. PLoS Negl Trop Dis 2023; 17:e0011173. [PMID: 36867651 PMCID: PMC10016652 DOI: 10.1371/journal.pntd.0011173] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 03/15/2023] [Accepted: 02/14/2023] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND Despite the use of numerous methods of control measures, mosquito populations and mosquito-borne diseases are still increasing globally. Evidence-based action thresholds to initiate or intensify control activities have been identified as essential in reducing mosquito populations to required levels at the correct/optimal time. This systematic review was conducted to identify different mosquito control action thresholds existing across the world and associated surveillance and implementation characteristics. METHODOLOGY/PRINCIPAL FINDINGS Searches for literature published from 2010 up to 2021 were performed using two search engines, Google Scholar and PubMed Central, according to PRISMA guidelines. A set of inclusion/exclusion criteria were identified and of the 1,485 initial selections, only 87 were included in the final review. Thirty inclusions reported originally generated thresholds. Thirteen inclusions were with statistical models that seemed intended to be continuously utilized to test the exceedance of thresholds in a specific region. There was another set of 44 inclusions that solely mentioned previously generated thresholds. The inclusions with "epidemiological thresholds" outnumbered those with "entomological thresholds". Most of the inclusions came from Asia and those thresholds were targeted toward Aedes and dengue control. Overall, mosquito counts (adult and larval) and climatic variables (temperature and rainfall) were the most used parameters in thresholds. The associated surveillance and implementation characteristics of the identified thresholds are discussed here. CONCLUSIONS/SIGNIFICANCE The review identified 87 publications with different mosquito control thresholds developed across the world and published during the last decade. Associated surveillance and implementation characteristics will help organize surveillance systems targeting the development and implementation of action thresholds, as well as direct awareness towards already existing thresholds for those with programs lacking available resources for comprehensive surveillance systems. The findings of the review highlight data gaps and areas of focus to fill in the action threshold compartment of the IVM toolbox.
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Affiliation(s)
- Vindhya S. Aryaprema
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Madeline R. Steck
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Steven T. Peper
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Rui-de Xue
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Whitney A. Qualls
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
- * E-mail:
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Stein RA, Grayon A, Katz A, Chervenak FA. The Zika virus: an opportunity to revisit reproductive health needs and disparities. Germs 2022; 12:519-537. [PMID: 38021183 PMCID: PMC10660223 DOI: 10.18683/germs.2022.1357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/24/2022] [Accepted: 12/29/2022] [Indexed: 12/01/2023]
Abstract
First isolated in 1947, the Zika virus was initially connected only to limited or sporadic human infections. In late 2015, the temporal clustering of a Zika outbreak and microcephaly in newborn babies from northeastern Brazil, and the identification of a causal link between the two, led to the characterization of the congenital Zika syndrome. In the wake of the epidemic, several countries from Latin America advised women to postpone pregnancies for periods ranging from six months to two years. These recommendations initiated critical conversations about the challenges of implementing them in societies with limited access to contraception, widespread socioeconomic inequalities, and high rates of unplanned and adolescent pregnancies. The messaging targeted exclusively women, despite a high prevalence of imbalances in the relationship power, and addressed all women as a group, failing to recognize that the decision to postpone pregnancies will impact different women in different ways, depending on their age at the time. Finally, in several countries affected by the Zika epidemic, due to restrictive reproductive policies, legally terminating a pregnancy is no longer an option even at the earliest time when brain malformations as part of the congenital Zika syndrome can be detected by ultrasonography. The virus continued to circulate after 2016 in several countries. Climate change models predict an expansion of the geographical area where local Zika transmission may occur, indicating that the interface between the virus, teratogenesis, and reproductive rights is a topic of considerable interest for medicine, social sciences, and public health for years to come.
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Affiliation(s)
- Richard A. Stein
- MD, PhD, NYU Tandon School of Engineering, Department of Chemical and Biomolecular Engineering, 6 MetroTech Center, Brooklyn 11201, NY, USA
| | - Alexis Grayon
- NYU Tandon School of Engineering, Department of Chemical and Biomolecular Engineering, 6 MetroTech Center, Brooklyn 11201, NY, USA
| | - Adi Katz
- MD, Department of Obstetrics and Gynecology, Lenox Hill Hospital, Donald and Barbara Zucker School of Medicine at Hofstra Northwell, 110 E 77th Street, New York, NY, 10075, USA
| | - Frank A. Chervenak
- MD, Department of Obstetrics and Gynecology, Lenox Hill Hospital, Donald and Barbara Zucker School of Medicine at Hofstra Northwell, 110 E 77th Street, New York, NY, 10075, USA
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Pascoe L, Clemen T, Bradshaw K, Nyambo D. Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15578. [PMID: 36497652 PMCID: PMC9740748 DOI: 10.3390/ijerph192315578] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
The study sought to review the works of literature on agent-based modeling and the influence of climatic and environmental factors on disease outbreak, transmission, and surveillance. Thus, drawing the influence of environmental variables such as vegetation index, households, mosquito habitats, breeding sites, and climatic variables including precipitation or rainfall, temperature, wind speed, and relative humidity on dengue disease modeling using the agent-based model in an African context and globally was the aim of the study. A search strategy was developed and used to search for relevant articles from four databases, namely, PubMed, Scopus, Research4Life, and Google Scholar. Inclusion criteria were developed, and 20 articles met the criteria and have been included in the review. From the reviewed works of literature, the study observed that climatic and environmental factors may influence the arbovirus disease outbreak, transmission, and surveillance. Thus, there is a call for further research on the area. To benefit from arbovirus modeling, it is crucial to consider the influence of climatic and environmental factors, especially in Africa, where there are limited studies exploring this phenomenon.
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Affiliation(s)
- Luba Pascoe
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
| | - Thomas Clemen
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
- Department of Computer Science, Hamburg University of Applied Sciences, Berliner Tor 7, 20099 Hamburg, Germany
| | - Karen Bradshaw
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
- Department of Computer Science, Rhodes University, Grahamstown 6139, South Africa
| | - Devotha Nyambo
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
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Myth surrounding the FDA disapproval of hydroxychloroquine sulfate and chloroquine phosphate as drugs for coronavirus disease 2019. CORONAVIRUS DRUG DISCOVERY 2022. [PMCID: PMC9217737 DOI: 10.1016/b978-0-323-85156-5.00002-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Chloroquine (CQ) and its analog hydroxychloroquine (HCQ) are popular antimalarial drugs that also exhibit wide range of activities against other diseases such as cancer, diabetes, HIV, and microbial infections, among others. They are also reported to possess antioxidant properties. The popularity of these drugs skyrocketed with the emergence of coronavirus disease 2019 (COVID-19) that has caused the deaths of over 600,000,000 people worldwide just within 7 months. Due to the urgency of the time in discovering or repurposing new drugs that will be active against SARS-CoV-2, the causative agent of COVID-19, some initial in vitro studies found prospects in CQ and HCQ against SARS-CoV-2. HCQ instantly became a drug of choice over CQ for the treatment of COVID-19 patients because it is readily absorbed and less toxic. However, clinical studies found no positive indices to support the continued use of HCQ. This chapter looks into this by consulting current literatures in order to unravel the myth surrounding the approval and disapproval of the use of HCQ.
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Imported arboviral infections in New Zealand, 2001 to 2017: A risk factor for local transmission. Travel Med Infect Dis 2021; 41:102047. [PMID: 33819569 DOI: 10.1016/j.tmaid.2021.102047] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 08/14/2020] [Accepted: 03/29/2021] [Indexed: 11/20/2022]
Abstract
BACKGROUND/AIMS Over the last decade and following international trends, cases of mosquito-borne arboviral infections, notably dengue fever, chikungunya and Zika, have increased among travellers arriving in New Zealand, but no locally acquired cases have been identified. Imported cases are characterised and examined to identify trends and features that might assist in reducing transmission risk from travellers. METHODS Information on traveller arrivals, notified cases and risk factors for disease acquisition were obtained from national sources. Trends in importation rates, seasonality are described and relationships of notifications with traveller arrivals were examined with a negative binomial regression model. RESULTS There was a significant increase in dengue notifications combined with the emergence of Zika and chikungunya. Most notifications were from arrivals in Auckland from Pacific Islands during summer and early autumn. CONCLUSION/IMPLICATIONS Overseas travel from New Zealand, particularly to the Pacific Islands and Southeast Asia, involves a risk of arboviral infection. The repeated introduction of arboviruses to New Zealand also increases the risk of local transmission in a country that has vector capable and vector potential mosquitoes, as well as an increasingly suitable climate for new vectors to establish.
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10
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Li SL, Messina JP, Pybus OG, Kraemer MUG, Gardner L. A review of models applied to the geographic spread of Zika virus. Trans R Soc Trop Med Hyg 2021; 115:956-964. [PMID: 33570155 PMCID: PMC8417088 DOI: 10.1093/trstmh/trab009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 12/13/2020] [Accepted: 01/08/2021] [Indexed: 11/13/2022] Open
Abstract
In recent years, Zika virus (ZIKV) has expanded its geographic range and in 2015–2016 caused a substantial epidemic linked to a surge in developmental and neurological complications in newborns. Mathematical models are powerful tools for assessing ZIKV spread and can reveal important information for preventing future outbreaks. We reviewed the literature and retrieved modelling studies that were developed to understand the spatial epidemiology of ZIKV spread and risk. We classified studies by type, scale, aim and applications and discussed their characteristics, strengths and limitations. We examined the main objectives of these models and evaluated the effectiveness of integrating epidemiological and phylogeographic data, along with socioenvironmental risk factors that are known to contribute to vector–human transmission. We also assessed the promising application of human mobility data as a real-time indicator of ZIKV spread. Lastly, we summarised model validation methods used in studies to ensure accuracy in models and modelled outcomes. Models are helpful for understanding ZIKV spread and their characteristics should be carefully considered when developing future modelling studies to improve arbovirus surveillance.
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Affiliation(s)
- Sabrina L Li
- School of Geography and the Environment, University of Oxford, South Parks Road, Oxford, OX1 3QY, UK
| | - Jane P Messina
- School of Geography and the Environment, University of Oxford, South Parks Road, Oxford, OX1 3QY, UK.,School of Global and Area Studies, University of Oxford, 12 Bevington Road, Oxford, OX2 6LH, UK
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, 11a Mansfield Rd, Oxford, OX1 3SZ, UK
| | - Moritz U G Kraemer
- Department of Zoology, University of Oxford, 11a Mansfield Rd, Oxford, OX1 3SZ, UK
| | - Lauren Gardner
- Department of Civil and Systems Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218-2682, USA.,Center for Systems Science and Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218-2682, USA
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11
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Sun Z, Di L, Sprigg W, Tong D, Casal M. Community venue exposure risk estimator for the COVID-19 pandemic. Health Place 2020; 66:102450. [PMID: 33010661 PMCID: PMC7522786 DOI: 10.1016/j.healthplace.2020.102450] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 09/11/2020] [Accepted: 09/17/2020] [Indexed: 12/16/2022]
Abstract
Complexities of virus genotypes and the stochastic contacts in human society create a big challenge for estimating the potential risks of exposure to a widely spreading virus such as COVID-19. To increase public awareness of exposure risks in daily activities, we propose a birthday-paradox-based probability model to implement in a web-based system, named COSRE (community social risk estimator) and make in-time community exposure risk estimation during the ongoing COVID-19 pandemic. We define exposure risk to mean the probability of people meeting potential cases in public places such as grocery stores, gyms, libraries, restaurants, coffee shops, offices, etc. Our model has three inputs: the real-time number of active and asymptomatic cases, the population in local communities, and the customer counts in the room. With COSRE, possible impacts of the pandemic can be explored through spatiotemporal analysis, e.g., a variable number of people may be projected into public places through time to assess changes of risk as the pandemic unfolds. The system has potential to advance understanding of the true exposure risks in various communities. It introduces an objective element to plan, prepare and respond during a pandemic. Spatial analysis tools are used to draw county-level exposure risks of the United States from April 1 to July 15, 2020. The correlation experiment with the new cases in the next two weeks shows that the risk estimation model offers promise in assisting people to be more precise about their personal safety and control of daily routine and social interaction. It can inform business and municipal COVID-19 policy to accelerate recovery.
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Affiliation(s)
- Ziheng Sun
- Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA; Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA, USA.
| | - Liping Di
- Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA; Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA, USA.
| | - William Sprigg
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA.
| | - Daniel Tong
- Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA; Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA, USA.
| | - Mariana Casal
- Infectious Disease and Epidemiology Section, Pinal County Health Department, Florence, AZ, USA.
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Kading RC, Cohnstaedt LW, Fall K, Hamer GL. Emergence of Arboviruses in the United States: The Boom and Bust of Funding, Innovation, and Capacity. Trop Med Infect Dis 2020; 5:E96. [PMID: 32517268 PMCID: PMC7345222 DOI: 10.3390/tropicalmed5020096] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 06/01/2020] [Accepted: 06/04/2020] [Indexed: 11/16/2022] Open
Abstract
Mosquito-borne viruses will continue to emerge and generate a significant public health burden around the globe. Here, we provide a longitudinal perspective on how the emergence of mosquito-borne viruses in the Americas has triggered reactionary funding by sponsored agencies, stimulating a number of publications, innovative development of traps, and augmented capacity. We discuss the return on investment (ROI) from the oscillation in federal funding that influences demand for surveillance and control traps and leads to innovation and research productivity.
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Affiliation(s)
- Rebekah C. Kading
- Department of Microbiology, Colorado State University, Immunology and Pathology, Fort Collins, Colorado, CO 80523, USA
| | - Lee W. Cohnstaedt
- United States Department of Agriculture, Arthropod-borne Animal Diseases Research Unit, Agricultural Research Service, Manhattan, Kansas, KS 66502, USA;
| | - Ken Fall
- BioQuip Products, Rancho Dominguez, California, CA 90220, USA;
| | - Gabriel L. Hamer
- Department of Entomology, College of Agriculture and Life Sciences, Texas A&M University, College Station, Texas, TX 77843, USA;
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Mina MJ, Guterman LB, Allen KE, Omer SB. Comprehensive Profiling of Zika Virus Risk with Natural and Artificial Mitigating Strategies, United States. Emerg Infect Dis 2020; 26:700-710. [PMID: 32043959 PMCID: PMC7101119 DOI: 10.3201/eid2604.181739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Zika virus is transitioning to become a long-term public health challenge, and countries should remain informed of the risk for emergence. We developed a stochastic epidemiologic model to profile risk for Zika virus emergence, including trimester-specific fetal risk across time, in all 3,208 counties in the United States, including Puerto Rico. Validation against known transmission in North America demonstrated accuracy to predict epidemic dynamics and absolute case counts across scales (R2 = 0.98). We found that, although sporadic single transmission events could occur in most US counties, outbreaks will likely be restricted to the Gulf Coast region and to late spring through autumn. Seasonal fluctuations in birth rates will confer natural population-level protection against early-trimester infections. Overall, outbreak control will be more effective and efficient than prevention, and vaccination will be most effective at >70% coverage. Our county-level risk profiles should serve as a critical resource for resource allocation.
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14
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Chowell G, Mizumoto K, Banda JM, Poccia S, Perrings C. Assessing the potential impact of vector-borne disease transmission following heavy rainfall events: a mathematical framework. Philos Trans R Soc Lond B Biol Sci 2020; 374:20180272. [PMID: 31056044 PMCID: PMC6553605 DOI: 10.1098/rstb.2018.0272] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Predicting the impact of natural disasters such as hurricanes on the transmission dynamics of infectious diseases poses significant challenges. In this paper, we put forward a simple modelling framework to investigate the impact of heavy rainfall events (HREs) on mosquito-borne disease transmission in temperate areas of the world such as the southern coastal areas of the USA. In particular, we explore the impact of the timing of HREs relative to the transmission season via analyses that test the sensitivity of HRE-induced epidemics to variation in the effects of rainfall on the dynamics of mosquito breeding capacity, and the intensity and temporal profile of human population displacement patterns. The recent Hurricane Harvey in Texas motivates the simulations reported. Overall, we find that the impact of vector-borne disease transmission is likely to be greater the earlier the HREs occur in the transmission season. Simulations based on data for Hurricane Harvey suggest that the limited impact it had on vector-borne disease transmission was in part because of when it occurred (late August) relative to the local transmission season, and in part because of the mitigating effect of the displacement of people. We also highlight key data gaps related to models of vector-borne disease transmission in the context of natural disasters. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.
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Affiliation(s)
- G Chowell
- 1 Department of Population Health Sciences, School of Public Health, Georgia State University , Atlanta, GA 30303 , USA
| | - K Mizumoto
- 1 Department of Population Health Sciences, School of Public Health, Georgia State University , Atlanta, GA 30303 , USA
| | - J M Banda
- 2 Computer Science Department, Georgia State University , Atlanta, GA 30303 , USA
| | - S Poccia
- 3 Computer Science Department, University of Turin , 10124 Turin, Italy
| | - C Perrings
- 4 School of Life Sciences, Arizona State University , Tempe, AZ 85281 , USA
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Kobres PY, Chretien JP, Johansson MA, Morgan JJ, Whung PY, Mukundan H, Del Valle SY, Forshey BM, Quandelacy TM, Biggerstaff M, Viboud C, Pollett S. A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern. PLoS Negl Trop Dis 2019; 13:e0007451. [PMID: 31584946 PMCID: PMC6805005 DOI: 10.1371/journal.pntd.0007451] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 10/22/2019] [Accepted: 08/27/2019] [Indexed: 01/04/2023] Open
Abstract
INTRODUCTION Epidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible, and actionable the information produced by these studies was. METHODS To improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE, and grey literature review, we identified studies that forecasted, predicted, or simulated ecological or epidemiological phenomena related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility, and clarity by independent reviewers. RESULTS 2034 studies were identified, of which n = 73 met the eligibility criteria. Spatial spread, R0 (basic reproductive number), and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barré Syndrome burden (4%), sexual transmission risk (4%), and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%), and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions, and 54% provided sufficient methodological detail to allow complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median of 119 days sooner than journal publication dates, they were used in only 30% of studies. CONCLUSIONS Many ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics, and pandemics.
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Affiliation(s)
- Pei-Ying Kobres
- School of Public Health, George Washington University, Washington, DC, United States of America
| | | | - Michael A. Johansson
- Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, Atlanta, Georgia, United States of America
| | - Jeffrey J. Morgan
- Joint Research and Development Inc, Stafford, Virginia, United States of America
| | - Pai-Yei Whung
- Office of Research & Development, US Environmental Protection Agency, Washington, DC, United States of America
| | - Harshini Mukundan
- Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Sara Y. Del Valle
- Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Brett M. Forshey
- Armed Forces Health Surveillance Branch, Silver Spring, Maryland, United States of America
| | - Talia M. Quandelacy
- Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, Atlanta, Georgia, United States of America
- Johns Hopkins School of Public Health, Baltimore, Maryland, United States of America
| | - Matthew Biggerstaff
- Influenza Division, Centers for Disease Control & Prevention, Atlanta, Georgia, United States of America
| | - Cecile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Simon Pollett
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America
- Department of Preventive Medicine & Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America
- Marie Bashir Institute, University of Sydney, Sydney, New South Wales, Australia
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16
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Modelling microbial infection to address global health challenges. Nat Microbiol 2019; 4:1612-1619. [PMID: 31541212 PMCID: PMC6800015 DOI: 10.1038/s41564-019-0565-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 08/15/2019] [Indexed: 12/20/2022]
Abstract
The continued growth of the world’s population and increased interconnectivity heighten the risk that infectious diseases pose for human health worldwide. Epidemiological modelling is a tool that can be used to mitigate this risk by predicting disease spread or quantifying the impact of different intervention strategies on disease transmission dynamics. We illustrate how four decades of methodological advances and improved data quality have facilitated the contribution of modelling to address global health challenges, exemplified by models for the HIV crisis, emerging pathogens and pandemic preparedness. Throughout, we discuss the importance of designing a model that is appropriate to the research question and the available data. We highlight pitfalls that can arise in model development, validation and interpretation. Close collaboration between empiricists and modellers continues to improve the accuracy of predictions and the optimization of models for public health decision-making.
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17
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Fox SJ, Bellan SE, Perkins TA, Johansson MA, Meyers LA. Downgrading disease transmission risk estimates using terminal importations. PLoS Negl Trop Dis 2019; 13:e0007395. [PMID: 31199809 PMCID: PMC6594658 DOI: 10.1371/journal.pntd.0007395] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 06/26/2019] [Accepted: 04/16/2019] [Indexed: 12/19/2022] Open
Abstract
As emerging and re-emerging infectious arboviruses like dengue, chikungunya, and Zika threaten new populations worldwide, officials scramble to assess local severity and transmissibility, with little to no epidemiological history to draw upon. Indirect estimates of risk from vector habitat suitability maps are prone to great uncertainty, while direct estimates from epidemiological data are only possible after cases accumulate and, given environmental constraints on arbovirus transmission, cannot be widely generalized beyond the focal region. Combining these complementary methods, we use disease importation and transmission data to improve the accuracy and precision of a priori ecological risk estimates. We demonstrate this approach by estimating the spatiotemporal risks of Zika virus transmission throughout Texas, a high-risk region in the southern United States. Our estimates are, on average, 80% lower than published ecological estimates-with only six of 254 Texas counties deemed capable of sustaining a Zika epidemic-and they are consistent with the number of autochthonous cases detected in 2017. Importantly our method provides a framework for model comparison, as our mechanistic understanding of arbovirus transmission continues to improve. Real-time updating of prior risk estimates as importations and outbreaks arise can thereby provide critical, early insight into local transmission risks as emerging arboviruses expand their global reach.
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Affiliation(s)
- Spencer J. Fox
- Department of Integrative Biology, University of Texas at Austin, Austin, Texas, United States of America
| | - Steven E. Bellan
- Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia, United States of America
- Center for Ecology of Infectious Diseases, University of Georgia, Athens, Gerogia, United States of America
| | - T. Alex Perkins
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Michael A. Johansson
- Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
- Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Lauren Ancel Meyers
- Department of Integrative Biology, University of Texas at Austin, Austin, Texas, United States of America
- Santa Fe Institute, Santa Fe, New Mexico, United States of America
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18
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Chen X, Dimitrov NB, Meyers LA. Uncertainty analysis of species distribution models. PLoS One 2019; 14:e0214190. [PMID: 31120909 PMCID: PMC6533036 DOI: 10.1371/journal.pone.0214190] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2017] [Accepted: 03/09/2019] [Indexed: 11/19/2022] Open
Abstract
The maximum entropy model, a commonly used species distribution model (SDM) normally combines observations of the species occurrence with environmental information to predict the geographic distributions of animal or plant species. However, it only produces point estimates for the probability of species existence. To understand the uncertainty of the point estimates, we analytically derived the variance of the outputs of the maximum entropy model from the variance of the input. We applied the analytic method to obtain the standard deviation of dengue importation probability and Aedes aegypti suitability. Dengue occurrence data and Aedes aegypti mosquito abundance data, combined with demographic and environmental data, were applied to obtain point estimates and the corresponding variance. To address the issue of not having the true distributions for comparison, we compared and contrasted the performance of the analytical expression with the bootstrap method and Poisson point process model which proved of equivalence of maximum entropy model with the assumption of independent point locations. Both Dengue importation probability and Aedes aegypti mosquito suitability examples show that the methods generate comparatively the same results and the analytic method we introduced is dramatically faster than the bootstrap method and directly apply to maximum entropy model.
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Affiliation(s)
- Xi Chen
- Graduate Program in Operations Research Industrial Engineering, The University of Texas at Austin, Austin, Texas, United States of America
| | - Nedialko B. Dimitrov
- Graduate Program in Operations Research Industrial Engineering, The University of Texas at Austin, Austin, Texas, United States of America
| | - Lauren Ancel Meyers
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
- The Santa Fe Institute, Santa Fe, New Mexico, United States of America
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19
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Ferdousi T, Cohnstaedt LW, McVey DS, Scoglio CM. Understanding the survival of Zika virus in a vector interconnected sexual contact network. Sci Rep 2019; 9:7253. [PMID: 31076660 PMCID: PMC6510745 DOI: 10.1038/s41598-019-43651-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 04/26/2019] [Indexed: 12/25/2022] Open
Abstract
The recent outbreaks of the insect-vectored Zika virus have demonstrated its potential to be sexually transmitted, which complicates modeling and our understanding of disease dynamics. Autochthonous outbreaks in the US mainland may be a consequence of both modes of transmission, which affect the outbreak size, duration, and virus persistence. We propose a novel individual-based interconnected network model that incorporates both insect-vectored and sexual transmission of this pathogen. This model interconnects a homogeneous mosquito vector population with a heterogeneous human host contact network. The model incorporates the seasonal variation of mosquito abundance and characterizes host dynamics based on age group and gender in order to produce realistic projections. We use a sexual contact network which is generated on the basis of real world sexual behavior data. Our findings suggest that for a high relative transmissibility of asymptomatic hosts, Zika virus shows a high probability of sustaining in the human population for up to 3 months without the presence of mosquito vectors. Zika outbreaks are strongly affected by the large proportion of asymptomatic individuals and their relative transmissibility. The outbreak size is also affected by the time of the year when the pathogen is introduced. Although sexual transmission has a relatively low contribution in determining the epidemic size, it plays a role in sustaining the epidemic and creating potential endemic scenarios.
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Affiliation(s)
- Tanvir Ferdousi
- Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS, 66506, USA.
| | - Lee W Cohnstaedt
- Arthropod-Borne Animal Diseases Research Unit, Center for Grain and Animal Health Research, USDA, Manhattan, KS, 66502, USA
| | - D S McVey
- Arthropod-Borne Animal Diseases Research Unit, Center for Grain and Animal Health Research, USDA, Manhattan, KS, 66502, USA
| | - Caterina M Scoglio
- Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS, 66506, USA
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Duncan R, Grigorenko E, Fisher C, Hockman D, Lanning B. Advances in multiplex nucleic acid diagnostics for blood-borne pathogens: promises and pitfalls - an update. Expert Rev Mol Diagn 2018; 19:15-25. [DOI: 10.1080/14737159.2019.1559055] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Robert Duncan
- Center for Biologics Evaluation and Research, US FDA, Silver Spring, MD, USA
| | | | - Carolyn Fisher
- Center for Biologics Evaluation and Research, US FDA, Silver Spring, MD, USA
| | | | - Bryan Lanning
- Center for Biologics Evaluation and Research, US FDA, Silver Spring, MD, USA
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21
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Sun K, Zhang Q, Pastore-Piontti A, Chinazzi M, Mistry D, Dean NE, Rojas DP, Merler S, Poletti P, Rossi L, Halloran ME, Longini IM, Vespignani A. Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015-2016 ZIKV epidemic. BMC Med 2018; 16:195. [PMID: 30336778 PMCID: PMC6194624 DOI: 10.1186/s12916-018-1185-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 09/28/2018] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Local mosquito-borne Zika virus (ZIKV) transmission has been reported in two counties in the contiguous United States (US), prompting the issuance of travel, prevention, and testing guidance across the contiguous US. Large uncertainty, however, surrounds the quantification of the actual risk of ZIKV introduction and autochthonous transmission across different areas of the US. METHODS We present a framework for the projection of ZIKV autochthonous transmission in the contiguous US during the 2015-2016 epidemic using a data-driven stochastic and spatial epidemic model accounting for seasonal, environmental, and detailed population data. The model generates an ensemble of travel-related case counts and simulates their potential to have triggered local transmission at the individual level in the 2015-2016 ZIKV epidemic. RESULTS We estimate the risk of ZIKV introduction and local transmission at the county level and at the 0.025° × 0.025° cell level across the contiguous US. We provide a risk measure based on the probability of observing local transmission in a specific location during a ZIKV epidemic modeled after the epidemic observed during the years 2015-2016. The high spatial and temporal resolution of the model allows us to generate statistical estimates of the number of ZIKV introductions leading to local transmission in each location. We find that the risk was spatially heterogeneously distributed and concentrated in a few specific areas that account for less than 1% of the contiguous US population. Locations in Texas and Florida that have actually experienced local ZIKV transmission were among the places at highest risk according to our results. We also provide an analysis of the key determinants for local transmission and identify the key introduction routes and their contributions to ZIKV transmission in the contiguous US. CONCLUSIONS This framework provides quantitative risk estimates, fully captures the stochasticity of ZIKV introduction events, and is not biased by the under-ascertainment of cases due to asymptomatic cases. It provides general information on key risk determinants and data with potential uses in defining public health recommendations and guidance about ZIKV risk in the US.
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Affiliation(s)
- Kaiyuan Sun
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, 02115, USA
| | - Qian Zhang
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, 02115, USA
| | - Ana Pastore-Piontti
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, 02115, USA
| | - Matteo Chinazzi
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, 02115, USA
| | - Dina Mistry
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, 02115, USA
| | - Natalie E Dean
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, 32611, USA
| | - Diana Patricia Rojas
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, 32611, USA
| | | | | | - Luca Rossi
- Institute for Scientific Interchange Foundation, 10126, Turin, Italy
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, 98109, USA
- Department of Biostatistics, University of Washington, Seattle, 98195, USA
| | - Ira M Longini
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, 32611, USA
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, 02115, USA.
- Institute for Scientific Interchange Foundation, 10126, Turin, Italy.
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22
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Arora N, Banerjee AK, Narasu ML. Zika outbreak aftermath: status, progress, concerns and new insights. Future Virol 2018. [DOI: 10.2217/fvl-2018-0040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Zika, a neurotrophic virus belonging to Flaviviridae family of viruses and transmitted by vector mosquitoes of Aedes species, took the world by storm during its recent outbreak. Its spread to newer territories, unprecedented pace of transmission, lack of existing therapeutic agents and vaccines and an empty drug pipeline raised an alarm. Uncertainty about full spectrum of diseases and its long-term consequences, newly discovered modes of transmission and controversies over vector status of mosquito species like Culex quinquefasciatus led to layers of complexity and presented new hurdles and challenges in Zika virus research. This review summarizes the progress and updates of efforts, concerns, financial burden and available resources in light of newly acquired knowledge in Zika virus research.
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Affiliation(s)
- Neelima Arora
- Centre for Biotechnology, Institute of Science & Technology (Autonomous), Jawaharlal Nehru Technological University-Hyderabad, Kukatpally, Hyderabad 500085, Telangana, India
| | - Amit K Banerjee
- Biology Division, CSIR-Indian Institute of Chemical Technology, Uppal Road, Tarnaka, Hyderabad 500007, Telangana, India
| | - Mangamoori L Narasu
- Centre for Biotechnology, Institute of Science & Technology (Autonomous), Jawaharlal Nehru Technological University-Hyderabad, Kukatpally, Hyderabad 500085, Telangana, India
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23
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Wilder-Smith A, Vannice K, Durbin A, Hombach J, Thomas SJ, Thevarjan I, Simmons CP. Zika vaccines and therapeutics: landscape analysis and challenges ahead. BMC Med 2018; 16:84. [PMID: 29871628 PMCID: PMC5989336 DOI: 10.1186/s12916-018-1067-x] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Accepted: 05/01/2018] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Various Zika virus (ZIKV) vaccine candidates are currently in development. Nevertheless, unique challenges in clinical development and regulatory pathways may hinder the licensure of high-quality, safe, and effective ZIKV vaccines. DISCUSSION Implementing phase 3 efficacy trials will be difficult given the challenges of the spatio-temporal heterogeneity of ZIKV transmission, the unpredictability of ZIKV epidemics, the broad spectrum of clinical manifestations making a single definite endpoint difficult, a lack of sensitive and specific diagnostic assays, and the need for inclusion of vulnerable target populations. In addition to a vaccine, drugs for primary prophylaxis, post-exposure prophylaxis, or treatment should also be developed to prevent or mitigate the severity of congenital Zika syndrome. CONCLUSION Establishing the feasibility of immune correlates and/or surrogates are a priority. Given the challenges in conducting phase 3 trials at a time of waning incidence, human challenge trials should be considered to evaluate efficacy. Continued financial support and engagement of industry partners will be essential to the successful development, licensure, and accessibility of Zika vaccines or therapeutics.
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Affiliation(s)
- Annelies Wilder-Smith
- Immunization, Vaccines & Biologicals, World Health Organization, Geneva, Switzerland. .,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. .,Department of Epidemiology and Global Health, Umea University, Umea, Sweden.
| | - Kirsten Vannice
- Immunization, Vaccines & Biologicals, World Health Organization, Geneva, Switzerland
| | - Anna Durbin
- Center for Immunization Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Joachim Hombach
- Immunization, Vaccines & Biologicals, World Health Organization, Geneva, Switzerland
| | - Stephen J Thomas
- State University of New York, Upstate Medical University, Syracuse, NY, USA
| | - Irani Thevarjan
- Doherty Institute for Infection and Immunity, Parkville, VIC, 3010, Australia.,The Royal Melbourne Hospital, Parkville, VIC, 3010, Australia
| | - Cameron P Simmons
- Oxford University Clinical Research Unit, 764 Vo Van Kiet street, District 5, Ho Chi Minh City, Vietnam.,Institute of Vector-borne Disease, Monash University, Melbourne, VIC, Australia
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24
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Current and Future Use of Chloroquine and Hydroxychloroquine in Infectious, Immune, Neoplastic, and Neurological Diseases: A Mini-Review. Clin Drug Investig 2018; 38:653-671. [DOI: 10.1007/s40261-018-0656-y] [Citation(s) in RCA: 180] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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25
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Wiratsudakul A, Suparit P, Modchang C. Dynamics of Zika virus outbreaks: an overview of mathematical modeling approaches. PeerJ 2018; 6:e4526. [PMID: 29593941 PMCID: PMC5866925 DOI: 10.7717/peerj.4526] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 03/02/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The Zika virus was first discovered in 1947. It was neglected until a major outbreak occurred on Yap Island, Micronesia, in 2007. Teratogenic effects resulting in microcephaly in newborn infants is the greatest public health threat. In 2016, the Zika virus epidemic was declared as a Public Health Emergency of International Concern (PHEIC). Consequently, mathematical models were constructed to explicitly elucidate related transmission dynamics. SURVEY METHODOLOGY In this review article, two steps of journal article searching were performed. First, we attempted to identify mathematical models previously applied to the study of vector-borne diseases using the search terms "dynamics," "mathematical model," "modeling," and "vector-borne" together with the names of vector-borne diseases including chikungunya, dengue, malaria, West Nile, and Zika. Then the identified types of model were further investigated. Second, we narrowed down our survey to focus on only Zika virus research. The terms we searched for were "compartmental," "spatial," "metapopulation," "network," "individual-based," "agent-based" AND "Zika." All relevant studies were included regardless of the year of publication. We have collected research articles that were published before August 2017 based on our search criteria. In this publication survey, we explored the Google Scholar and PubMed databases. RESULTS We found five basic model architectures previously applied to vector-borne virus studies, particularly in Zika virus simulations. These include compartmental, spatial, metapopulation, network, and individual-based models. We found that Zika models carried out for early epidemics were mostly fit into compartmental structures and were less complicated compared to the more recent ones. Simple models are still commonly used for the timely assessment of epidemics. Nevertheless, due to the availability of large-scale real-world data and computational power, recently there has been growing interest in more complex modeling frameworks. DISCUSSION Mathematical models are employed to explore and predict how an infectious disease spreads in the real world, evaluate the disease importation risk, and assess the effectiveness of intervention strategies. As the trends in modeling of infectious diseases have been shifting towards data-driven approaches, simple and complex models should be exploited differently. Simple models can be produced in a timely fashion to provide an estimation of the possible impacts. In contrast, complex models integrating real-world data require more time to develop but are far more realistic. The preparation of complicated modeling frameworks prior to the outbreaks is recommended, including the case of future Zika epidemic preparation.
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Affiliation(s)
- Anuwat Wiratsudakul
- Department of Clinical Sciences and Public Health, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand
- The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand
| | - Parinya Suparit
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Ratchathewi, Bangkok, Thailand
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Ratchathewi, Bangkok, Thailand
- Centre of Excellence in Mathematics, CHE, Ratchathewi, Bangkok, Thailand
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Carlson CJ, Dougherty E, Boots M, Getz W, Ryan SJ. Consensus and conflict among ecological forecasts of Zika virus outbreaks in the United States. Sci Rep 2018; 8:4921. [PMID: 29563545 PMCID: PMC5862882 DOI: 10.1038/s41598-018-22989-0] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 03/02/2018] [Indexed: 12/11/2022] Open
Abstract
Ecologists are increasingly involved in the pandemic prediction process. In the course of the Zika outbreak in the Americas, several ecological models were developed to forecast the potential global distribution of the disease. Conflicting results produced by alternative methods are unresolved, hindering the development of appropriate public health forecasts. We compare ecological niche models and experimentally-driven mechanistic forecasts for Zika transmission in the continental United States. We use generic and uninformed stochastic county-level simulations to demonstrate the downstream epidemiological consequences of conflict among ecological models, and show how assumptions and parameterization in the ecological and epidemiological models propagate uncertainty and produce downstream model conflict. We conclude by proposing a basic consensus method that could resolve conflicting models of potential outbreak geography and seasonality. Our results illustrate the usually-undocumented margin of uncertainty that could emerge from using any one of these predictions without reservation or qualification. In the short term, ecologists face the task of developing better post hoc consensus that accurately forecasts spatial patterns of Zika virus outbreaks. Ultimately, methods are needed that bridge the gap between ecological and epidemiological approaches to predicting transmission and realistically capture both outbreak size and geography.
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Affiliation(s)
- Colin J Carlson
- National Socio-Environmental Synthesis Center, University of Maryland, Annapolis, MD, 21401, USA.
- Department of Biology, Georgetown University, Washington, DC, 20057, USA.
| | - Eric Dougherty
- Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA, 94720-3112, USA
| | - Mike Boots
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, 94720-3112, USA
| | - Wayne Getz
- Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA, 94720-3112, USA
- Schools of Mathematical Sciences, University of KwaZulu, Natal, South Africa
| | - Sadie J Ryan
- Schools of Life Sciences, University of KwaZulu, Natal, South Africa
- Department of Geography, University of Florida, Gainesville, FL, 32601, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32610, USA
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Dolley S. Big Data's Role in Precision Public Health. Front Public Health 2018; 6:68. [PMID: 29594091 PMCID: PMC5859342 DOI: 10.3389/fpubh.2018.00068] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 02/20/2018] [Indexed: 01/01/2023] Open
Abstract
Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.
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Shiryaev SA, Mesci P, Pinto A, Fernandes I, Sheets N, Shresta S, Farhy C, Huang CT, Strongin AY, Muotri AR, Terskikh AV. Repurposing of the anti-malaria drug chloroquine for Zika Virus treatment and prophylaxis. Sci Rep 2017; 7:15771. [PMID: 29150641 PMCID: PMC5694003 DOI: 10.1038/s41598-017-15467-6] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Accepted: 10/17/2017] [Indexed: 01/19/2023] Open
Abstract
One of the major challenges of the current Zika virus (ZIKV) epidemic is to prevent congenital foetal abnormalities, including microcephaly, following ZIKV infection of pregnant women. Given the urgent need for ZIKV prophylaxis and treatment, repurposing of approved drugs appears to be a viable and immediate solution. We demonstrate that the common anti-malaria drug chloroquine (CQ) extends the lifespan of ZIKV-infected interferon signalling-deficient AG129 mice. However, the severity of ZIKV infection in these mice precludes the study of foetal (vertical) viral transmission. Here, we show that interferon signalling-competent SJL mice support chronic ZIKV infection. Infected dams and sires are both able to transmit ZIKV to the offspring, making this an ideal model for in vivo validation of compounds shown to suppress ZIKV in cell culture. Administration of CQ to ZIKV-infected pregnant SJL mice during mid-late gestation significantly attenuated vertical transmission, reducing the ZIKV load in the foetal brain more than 20-fold. Given the limited side effects of CQ, its lack of contraindications in pregnant women, and its worldwide availability and low cost, we suggest that CQ could be considered for the treatment and prophylaxis of ZIKV.
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Affiliation(s)
- Sergey A Shiryaev
- Sanford Burnham Prebys Medical Discovery Institute, 10901 N. Torrey Pines Rd., La Jolla, CA, 92037, USA
| | - Pinar Mesci
- University of California San Diego, School of Medicine, Department of Pediatrics/Rady Children's Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA, 92037-0695, USA
| | - Antonella Pinto
- Sanford Burnham Prebys Medical Discovery Institute, 10901 N. Torrey Pines Rd., La Jolla, CA, 92037, USA
| | - Isabella Fernandes
- University of California San Diego, School of Medicine, Department of Pediatrics/Rady Children's Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA, 92037-0695, USA
| | - Nicholas Sheets
- Division of Inflammation Biology, La Jolla Institute for Allergy & Immunology, La Jolla, CA, 92037, USA
| | - Sujan Shresta
- Division of Inflammation Biology, La Jolla Institute for Allergy & Immunology, La Jolla, CA, 92037, USA
| | - Chen Farhy
- Sanford Burnham Prebys Medical Discovery Institute, 10901 N. Torrey Pines Rd., La Jolla, CA, 92037, USA
| | - Chun-Teng Huang
- Sanford Burnham Prebys Medical Discovery Institute, 10901 N. Torrey Pines Rd., La Jolla, CA, 92037, USA
| | - Alex Y Strongin
- Sanford Burnham Prebys Medical Discovery Institute, 10901 N. Torrey Pines Rd., La Jolla, CA, 92037, USA
| | - Alysson R Muotri
- University of California San Diego, School of Medicine, Department of Pediatrics/Rady Children's Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA, 92037-0695, USA.
| | - Alexey V Terskikh
- Sanford Burnham Prebys Medical Discovery Institute, 10901 N. Torrey Pines Rd., La Jolla, CA, 92037, USA.
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