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BackgroundUnderstanding the risk of chikungunya virus (CHIKV) infection and rheumatic sequelae across populations, including travelers and the military, is critical. We leveraged healthcare delivery data of over 9 million U.S. Military Health System (MHS) beneficiaries to identify cases, and sampled controls, to estimate the risk of post-CHIKV rheumatic sequelae.Methodology/principal findingsMHS beneficiary CHIKV infections diagnosed 2014-2018 were identified from the Disease Reporting System internet, TRICARE Encounter Data Non-Institutional, and Comprehensive Ambulatory/Professional Encounter Record systems. Non-CHIKV controls were matched (1:4) by age, gender, beneficiary status, and encounter date. The frequency of comorbidities and incident rheumatic diagnoses through December 2018 were derived from International Classification of Diseases codes and compared between cases and controls. Poisson regression models estimated the association of CHIKV infection with rheumatic sequelae. We further performed a nested case-control study to estimate risk factors for post-CHIKV sequelae in those with prior CHIKV. 195 CHIKV cases were diagnosed between July 2014 and December 2018. The median age was 42 years, and 43.6% were active duty. 63/195 (32.3%) of CHIKV cases had an incident rheumatic diagnosis, including arthralgia, polyarthritis, polymyalgia rheumatica, and/or rheumatoid arthritis, compared to 156/780 (20.0%) of controls (p < 0.001). CHIKV infection remained associated with rheumatic sequelae (aRR = 1.579, p = 0.008) after adjusting for prior rheumatic disease and demography. Those with rheumatic CHIKV sequelae had a median 7 healthcare encounters (IQR 3-15). Among CHIKV infections, we found no association between post-CHIKV rheumatic sequelae and demography, service characteristics, or comorbidities.Conclusions/significanceCHIKV infection is uncommon but associated with rheumatic sequelae among MHS beneficiaries, with substantial healthcare requirements in a proportion of cases with such sequelae. No demographic, clinical, or occupational variables were associated with post-CHIKV rheumatic sequelae, suggesting that prediction of these complications is challenging in MHS beneficiaries. These findings are important context for future CHIKV vaccine decision making in this and other populations.

IntroductionWe sought to determine pre-infection correlates of protection against SARS-CoV-2 post-vaccine inzfections (PVI) acquired during the first Omicron wave in the United States.MethodsSerum and saliva samples from 176 vaccinated adults were collected from October to December of 2021, immediately before the Omicron wave, and assessed for SARS-CoV-2 Spike-specific IgG and IgA binding antibodies (bAb). Sera were also assessed for bAb using commercial assays, and for neutralization activity against several SARS-CoV-2 variants. PVI duration and severity, as well as risk and precautionary behaviors, were assessed by questionnaires.ResultsSerum anti-Spike IgG levels assessed by research assay, neutralization titers against Omicron subvariants, and low home risk scores correlated with protection against PVIs after multivariable regression analysis. Commercial assays did not perform as well as research assay, likely due to their lower dynamic range.DiscussionIn the 32 participants that developed PVI, anti-Spike IgG bAbs correlated with lower disease severity and shorter duration of illness.

Abstract Mayaro Virus (MAYV) is an emerging health threat in the Americas that can cause febrile illness as well as debilitating arthralgia or arthritis. To better understand the geographic distribution of MAYV risk, we developed a georeferenced database of MAYV occurrence based on peer-reviewed literature and unpublished reports. Here we present this compendium, which includes both point and polygon locations linked to occurrence data documented from its discovery in 1954 until 2022. We describe all methods used to develop the database including data collection, georeferencing, management and quality-control. We also describe a customized grading system used to assess the quality of each study included in our review. The result is a comprehensive, evidence-graded database of confirmed MAYV occurrence in humans, non-human animals, and arthropods to-date, containing 262 geo-positioned occurrences in total. This database - which can be updated over time - may be useful for local spill-over risk assessment, epidemiological modelling to understand key transmission dynamics and drivers of MAYV spread, as well as identification of major surveillance gaps.

Mayaro virus (MAYV) is a mosquito-borne Alphavirus that is widespread in South America. MAYV infection often presents with non-specific febrile symptoms but may progress to debilitating chronic arthritis or arthralgia. Despite the pandemic threat of MAYV, its true distribution remains unknown. The objective of this study was to clarify the geographic distribution of MAYV using an established risk mapping framework. This consisted of generating evidence consensus scores for MAYV presence, modeling the potential distribution of MAYV in select countries across Central and South America, and estimating the population residing in areas suitable for MAYV transmission. We compiled a georeferenced compendium of MAYV occurrence in humans, animals, and arthropods. Based on an established evidence consensus framework, we integrated multiple information sources to assess the total evidence supporting ongoing transmission of MAYV within each country in our study region. We then developed high resolution maps of the disease's estimated distribution using a boosted regression tree approach. Models were developed using nine climatic and environmental covariates that are related to the MAYV transmission cycle. Using the output of our boosted regression tree models, we estimated the total population living in regions suitable for MAYV transmission. The evidence consensus scores revealed high or very high evidence of MAYV transmission in several countries including Brazil (especially the states of Mato Grosso and Goiás), Venezuela, Peru, Trinidad and Tobago, and French Guiana. According to the boosted regression tree models, a substantial region of South America is suitable for MAYV transmission, including north and central Brazil, French Guiana, and Suriname. Some regions (e.g., Guyana) with only moderate evidence of known transmission were identified as highly suitable for MAYV. We estimate that approximately 58.9 million people (95% CI: 21.4-100.4) in Central and South America live in areas that may be suitable for MAYV transmission, including 46.2 million people (95% CI: 17.6-68.9) in Brazil. Our results may assist in prioritizing high-risk areas for vector control, human disease surveillance and ecological studies.

[This corrects the article DOI: 10.1371/journal.pmed.1003793.].

Abstract The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient participants between April 2020 and January 2021, in a multi-center prospective cohort study at 8 military hospitals across the United States. Plasma inflammatory protein biomarkers were measured in samples from 15 to 28 days post symptom onset. Topological Data Analysis (TDA) was used to identify patterns of inflammation, and associations with peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated using logistic regression. The study population (n = 129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct inflammatory biomarker clusters were identified and were associated with significant differences in peak disease severity (p

IntroductionNatural killer (NK) cells can both amplify and regulate immune responses to vaccination. Studies in humans and animals have observed NK cell activation within days after mRNA vaccination. In this study, we sought to determine if baseline NK cell frequencies, phenotype, or function correlate with antibody responses or inflammatory side effects induced by the Pfizer-BioNTech COVID-19 vaccine (BNT162b2).MethodsWe analyzed serum and peripheral blood mononuclear cells (PBMCs) from 188 participants in the Prospective Assessment of SARS-CoV-2 Seroconversion study, an observational study evaluating immune responses in healthcare workers. Baseline serum samples and PBMCs were collected from all participants prior to any SARS-CoV-2 infection or vaccination. Spike-specific IgG antibodies were quantified at one and six months post-vaccination by microsphere-based multiplex immunoassay. NK cell frequencies and phenotypes were assessed on pre-vaccination PBMCs from all participants by multi-color flow cytometry, and on a subset of participants at time points after the 1st and 2nd doses of BNT162b2. Inflammatory side effects were assessed by structured symptom questionnaires, and baseline NK cell functionality was quantified by an in vitro killing assay on participants that reported high or low post-vaccination symptom scores.ResultsKey observations include: 1) circulating NK cells exhibit evidence of activation in the week following vaccination, 2) individuals with high symptom scores after 1st vaccination had higher pre-vaccination NK cytotoxicity indices, 3) high pre-vaccination NK cell numbers were associated with lower spike-specific IgG levels six months after two BNT162b2 doses, and 4) expression of the inhibitory marker NKG2A on immature NK cells was associated with higher antibody responses 1 and 6 months post-vaccination.DiscussionThese results suggest that NK cell activation by BNT162b2 vaccination may contribute to vaccine-induced inflammatory symptoms and reduce durability of vaccine-induced antibody responses.

Abstract The SARS-CoV-2 pandemic prompts evaluation of recombination in human coronavirus (hCoV) evolution. We undertook recombination analyses of 158,118 public seasonal hCoV, SARS-CoV-1, SARS-CoV-2 and MERS-CoV genome sequences using the RDP4 software. We found moderate evidence for 8 SARS-CoV-2 recombination events, two of which involved the spike gene, and low evidence for one SARS-CoV-1 recombination event. Within MERS-CoV, 229E, OC43, NL63 and HKU1 datasets, we noted 7, 1, 9, 14, and 1 high-confidence recombination events, respectively. There was propensity for recombination breakpoints in the non-ORF1 region of the genome containing structural genes, and recombination severely skewed the temporal structure of these data, especially for NL63 and OC43. Bayesian time-scaled analyses on recombinant-free data indicated the sampled diversity of seasonal CoVs emerged in the last 70 years, with 229E displaying continuous lineage replacements. These findings emphasize the importance of genomic based surveillance to detect recombination in SARS-CoV-2, particularly if recombination may lead to immune evasion.

Dengue control approaches are best informed by granular spatial epidemiology of these viruses, yet reconstruction of inter- and intra-household transmissions is limited when analyzing case count, serologic, or genomic consensus sequence data. To determine viral spread on a finer spatial scale, we extended phylogenomic discrete trait analyses to reconstructions of house-to-house transmissions within a prospective cluster study in Kamphaeng Phet, Thailand. For additional resolution and transmission confirmation, we mapped dengue intra-host single nucleotide variants on the taxa of these time-scaled phylogenies. This approach confirmed 19 household transmissions and revealed that dengue disperses an average of 70 m per day between households in these communities. We describe an evolutionary biology framework for the resolution of dengue transmissions that cannot be differentiated based on epidemiologic and consensus genome data alone. This framework can be used as a public health tool to inform control approaches and enable precise tracing of dengue transmissions.

Abstract Background SARS-CoV-2 is a recently emerged pandemic coronavirus (CoV) capable of causing severe respiratory illness. However, a significant number of infected people present as asymptomatic or pauci-symptomatic. In this prospective assessment of at-risk healthcare workers (HCWs) we seek to determine whether pre-existing antibody or T cell responses to previous seasonal human coronavirus (HCoV) infections affect immunological or clinical responses to SARS-CoV-2 infection or vaccination. Methods A cohort of 300 healthcare workers, confirmed negative for SARS-CoV-2 exposure upon study entry, will be followed for up to 1 year with monthly serology analysis of IgM and IgG antibodies against the spike proteins of SARS-CoV-2 and the four major seasonal human coronavirus - HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63. Participants will complete monthly questionnaires that ask about Coronavirus Disease 2019 (COVID-19) exposure risks, and a standardized, validated symptom questionnaire (scoring viral respiratory disease symptoms, intensity and severity) at least twice monthly and any day when any symptoms manifest. SARS-CoV-2 PCR testing will be performed any time participants develop symptoms consistent with COVID-19. For those individuals that seroconvert and/or test positive by SARS-CoV-2 PCR, or receive the SARS-CoV-2 vaccine, additional studies of T cell activation and cytokine production in response to SARS-CoV-2 peptide pools and analysis of Natural Killer cell numbers and function will be conducted on that participant’s cryopreserved baseline peripheral blood mononuclear cells (PBMCs). Following the first year of this study we will further analyze those participants having tested positive for COVID-19, and/or having received an authorized/licensed SARS-CoV-2 vaccine, quarterly (year 2) and semi-annually (years 3 and 4) to investigate immune response longevity. Discussion This study will determine the frequency of asymptomatic and pauci-symptomatic SARS-CoV-2 infection in a cohort of at-risk healthcare workers. Baseline and longitudinal assays will determine the frequency and magnitude of anti-spike glycoprotein antibodies to the seasonal HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63, and may inform whether pre-existing antibodies to these human coronaviruses are associated with altered COVID-19 disease course. Finally, this study will evaluate whether pre-existing immune responses to seasonal HCoVs affect the magnitude and duration of antibody and T cell responses to SARS-CoV-2 vaccination, adjusting for demographic covariates.

Yellow fever virus (YFV) has a long history of impacting human health in South America. Mayaro virus (MAYV) is an emerging arbovirus of public health concern in the Neotropics and its full impact is yet unknown. Both YFV and MAYV are primarily maintained via a sylvatic transmission cycle but can be opportunistically transmitted to humans by the bites of infected forest dwelling Haemagogus janthinomys Dyar, 1921. To better understand the potential risk of YFV and MAYV transmission to humans, a more detailed understanding of this vector species' distribution is critical. This study compiled a comprehensive database of 177 unique Hg. janthinomys collection sites retrieved from the published literature, digitized museum specimens and publicly accessible mosquito surveillance data. Covariate analysis was performed to optimize a selection of environmental (topographic and bioclimatic) variables associated with predicting habitat suitability, and species distributions modelled across South America using a maximum entropy (MaxEnt) approach. Our results indicate that suitable habitat for Hg. janthinomys can be found across forested regions of South America including the Atlantic forests and interior Amazon.

Abstract Natural dengue virus (DENV) infections occur by mosquito bite but how the inoculation route affects the humoral immune response is unknown. We serologically profiled 20 non-human primates (NHP) from a prior study of DENV1 infection where animals were inoculated by mosquito (N = 10) or subcutaneous injection (N = 10). Using a comprehensive, densely tiled and highly redundant pan-flavivirus programmable phage library containing 91,562 overlapping 62 amino acid peptides, we produced a high-resolution map of linear peptide sequences enriched during DENV seroconversion. Profiles in mosquito-inoculated and subcutaneously-inoculated animals were similar up to 90 days after primary infection, but diverged at 1 year with differences in sero-reactivity in the Envelope (E; residues 215–406; p 99% of the observed sero-reactivity difference. Antibody breadth did not vary by mode of inoculation. The differential reactivity to E domain III seen by phage display validated orthogonally by ELISA, but did not correlate with late neutralization titers. Serological profiling of humoral immune responses to DENV infection in NHP by programmable phage display demonstrated durable differences in sero-reactivity by route of inoculation.

Abstract Background Campylobacter jejuni is a leading cause of bacterial diarrhea worldwide, and increasing rates of fluoroquinolone (FQ) resistance in C. jejuni are a major public health concern. The rapid detection and tracking of FQ resistance are critical needs in developing countries, as these antimicrobials are widely used against C. jejuni infections. Detection of point mutations at T86I in the gyrA gene by real-time polymerase chain reaction (RT-PCR) is a rapid detection tool that may improve FQ resistance tracking. Methods C. jejuni isolates obtained from children with diarrhea in Peru were tested by RT-PCR to detect point mutations at T86I in gyrA. Further confirmation was performed by sequencing of the gyrA gene. Results We detected point mutations at T86I in the gyrA gene in 100% (141/141) of C. jejuni clinical isolates that were previously confirmed as ciprofloxacin-resistant by E-test. No mutations were detected at T86I in gyrA in any ciprofloxacin-sensitive isolates. Conclusions Detection of T86I mutations in C. jejuni is a rapid, sensitive, and specific method to identify fluoroquinolone resistance in Peru. This detection approach could be broadly employed in epidemiologic surveillance, therefore reducing time and cost in regions with limited resources.

Understanding the burden and risk factors of dengue virus (DENV) infection in Puerto Rico is important for the prevention of dengue in local, traveler and military populations. Using sera from the Department of Defense Serum Repository, we estimated the prevalence and predictors of DENV seropositivity in those who had served in Puerto Rico, stratified by birth or prior residence ("birth/residence") in dengue-endemic versus non-endemic regions. We selected sera collected in early 2015 from 500 U.S. military members, a time-point also permitting detection of early cryptic Zika virus (ZIKV) circulation. 87.2% were born or resided in a DENV-endemic area before their military service in Puerto Rico. A high-throughput, flow-cytometry-based neutralization assay was employed to screen sera for ZIKV and DENV neutralizing antibodies, and confirmatory testing was done by plaque-reduction neutralization test (PRNT). We identified one Puerto Rico resident who seroconverted to ZIKV by June 2015, suggesting cryptic ZIKV circulation in Puerto Rico at least 4 months before the first reported cases. A further six PRNT-positive presumptive ZIKV infections which were resolved as DENV infections only by the use of paired sera. We noted 66.8% of the total study sample was DENV seropositive by early 2015. Logistic regression analysis indicated that birth/residence in a dengue non-endemic region (before military service in Puerto Rico) was associated with a lower odds of DENV exposure by January-June 2015 (aOR = 0.28, p = 0.001). Among those with birth/residence in a non-endemic country, we noted moderate evidence to support increase in odds of DENV exposure for each year of military service in Puerto Rico (aOR = 1.58, p = 0.06), but no association with age. In those with birth/residence in dengue-endemic regions (before military service in Puerto Rico), we noted that age (aOR = 1.04, p = 0.02), rather than duration of Puerto Rico service, was associated with dengue seropositivity, suggesting earlier lifetime DENV exposure. Our findings provide insights into the burden and predictors of DENV infection in local, traveler and military populations in Puerto Rico. Our study also highlights substantial PRNT ZIKV false-positivity when paired sera are not available, even during periods of very low ZIKV prevalence.

Improving our understanding of Mayaro virus (MAYV) ecology is critical to guide surveillance and risk assessment. We conducted a PRISMA-adherent systematic review of the published and grey literature to identify potential arthropod vectors and non-human animal reservoirs of MAYV. We searched PubMed/MEDLINE, Embase, Web of Science, SciELO and grey-literature sources including PAHO databases and dissertation repositories. Studies were included if they assessed MAYV virological/immunological measured occurrence in field-caught, domestic, or sentinel animals or in field-caught arthropods. We conducted an animal seroprevalence meta-analysis using a random effects model. We compiled granular georeferenced maps of non-human MAYV occurrence and graded the quality of the studies using a customized framework. Overall, 57 studies were eligible out of 1523 screened, published between the years 1961 and 2020. Seventeen studies reported MAYV positivity in wild mammals, birds, or reptiles and five studies reported MAYV positivity in domestic animals. MAYV positivity was reported in 12 orders of wild-caught vertebrates, most frequently in the orders Charadriiformes and Primate. Sixteen studies detected MAYV in wild-caught mosquito genera including Haemagogus, Aedes, Culex, Psorophora, Coquillettidia, and Sabethes. Vertebrate animals or arthropods with MAYV were detected in Brazil, Panama, Peru, French Guiana, Colombia, Trinidad, Venezuela, Argentina, and Paraguay. Among non-human vertebrates, the Primate order had the highest pooled seroprevalence at 13.1% (95% CI: 4.3-25.1%). From the three most studied primate genera we found the highest seroprevalence was in Alouatta (32.2%, 95% CI: 0.0-79.2%), followed by Callithrix (17.8%, 95% CI: 8.6-28.5%), and Cebus/Sapajus (3.7%, 95% CI: 0.0-11.1%). We further found that MAYV occurs in a wide range of vectors beyond Haemagogus spp. The quality of evidence behind these findings was variable and prompts calls for standardization of reporting of arbovirus occurrence. These findings support further risk emergence prediction, guide field surveillance efforts, and prompt further in-vivo studies to better define the ecological drivers of MAYV maintenance and potential for emergence.

BackgroundThe importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research.Methods and findingsWe developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies.ConclusionsThese guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.

Introduction: High quality epidemic forecasting and prediction are critical to support response to local, regional and global infectious disease threats. Other fields of biomedical research use consensus reporting guidelines to ensure standardization and quality of research practice among researchers, and to provide a framework for end-users to interpret the validity of study results. The purpose of this study was to determine whether guidelines exist specifically for epidemic forecast and prediction publications. Methods: We undertook a formal systematic review to identify and evaluate any published infectious disease epidemic forecasting and prediction reporting guidelines. This review leveraged a team of 18 investigators from US Government and academic sectors. Results: A literature database search through May 26, 2019, identified 1467 publications (MEDLINE n = 584, EMBASE n = 883), and a grey-literature review identified a further 407 publications, yielding a total 1777 unique publications. A paired-reviewer system screened in 25 potentially eligible publications, of which two were ultimately deemed eligible. A qualitative review of these two published reporting guidelines indicated that neither were specific for epidemic forecasting and prediction, although they described reporting items which may be relevant to epidemic forecasting and prediction studies. Conclusions: This systematic review confirms that no specific guidelines have been published to standardize the reporting of epidemic forecasting and prediction studies. These findings underscore the need to develop such reporting guidelines in order to improve the transparency, quality and implementation of epidemic forecasting and prediction research in operational public health.

Epidemics of emerging and re-emerging infectious diseases are a danger to civilian and military populations worldwide. Health security and mitigation of infectious disease threats is a priority of the United States Government and the Department of Defense (DoD). Next generation sequencing (NGS) and Bioinformatics (BI) enhances traditional biosurveillance by providing additional data to understand transmission, identify resistance and virulence factors, make predictions, and update risk assessments. As more and more laboratories adopt NGS and BI technologies they encounter challenges in building local capacity. In addition to choosing the right sequencing platform and approach, considerations must also be made for the complexity of bioinformatics analyses, data storage, as well as personnel and computational requirements. To address these needs, a comprehensive training program was developed covering wet lab and bioinformatics approaches to NGS. The program is meant to be modular and adaptive to meet both common and individualized needs of medical research and public health laboratories across the DoD. The training program was first deployed internationally to the Basic Science Laboratory of the US Army Medical Research Directorate-Africa in Kisumu, Kenya, which is an overseas Lab of the Walter Reed Army Institute of Research (WRAIR). A week-long workshop with intensive focus on targeted sequencing and the bioinformatics of genome assembly (n = 24 participants) was held. Post-workshop self-assessment (completed by 21 participants) noted significant median gains in knowledge domains related to NGS targeted sequencing, bioinformatics for genome assembly, and sequence quality assessment. The participants also reported that the information on study design, sample preparation, sequencing quality control, data quality assessment, reporting, and basic and advanced bioinformatics analysis were the most useful information presented in the training. While longer-term evaluations are planned, the training resulted in significant short-term improvement of a laboratory’s self-reported wet lab and bioinformatics capabilities. This framework can be used for future DoD laboratory development in the area of NGS and BI for infectious disease surveillance, ultimately enhancing this global DoD capability.

Infectious disease modeling has played a prominent role in recent outbreaks, yet integrating these analyses into public health decision-making has been challenging. We recommend establishing ‘outbreak science’ as an inter-disciplinary field to improve applied epidemic modeling.

IntroductionEpidemic 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.MethodsTo 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.Results2034 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.ConclusionsMany 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.

Zika virus (ZIKV) recently caused a pandemic complicated by Guillain-Barre syndrome (GBS) and birth defects. ZIKV is structurally similar to the dengue viruses (DENV) and in vitro studies suggest antibody dependent enhancement occurs in ZIKV infections preceded by DENV; however, the clinical significance of this remains unclear. We undertook a PRISMA-adherent systematic review of all current human and non-human primate (NHP) data to determine if prior infection with DENV, compared to DENV-naïve hosts, is associated with a greater risk of ZIKV clinical complications or greater ZIKV peak viremia in vivo. We identified 1146 studies in MEDLINE, EMBASE and the grey literature, of which five studies were eligible. One human study indicated no increase in the risk of GBS in ZIKV infections with prior DENV exposure. Two additional human studies showed a small increase in ZIKV viremia in those with prior DENV exposure; however, this was not statistically significant nor was it associated with an increase in clinical severity or adverse pregnancy outcomes. While no meta-analysis was possible using human data, a pooled analysis of the two NHP studies leveraging extended data provided only weak evidence of a 0.39 log10 GE/mL rise in ZIKV viremia in DENV experienced rhesus macaques compared to those with no DENV exposure (p = 0.22). Using a customized quality grading criteria, we further show that no existing published human studies have offered high quality measurement of both acute ZIKV and antecedent DENV infections. In conclusion, limited human and NHP studies indicate a small and non-statistically significant increase in ZIKV viremia in DENV-experienced versus DENV-naïve hosts; however, there is no evidence that even a possible small increase in ZIKV viremia would correlate with a change in ZIKV clinical phenotype. More data derived from larger sample sizes and improved sero-assays are needed to resolve this question, which has major relevance for clinical prognosis and vaccine design.

It remains unclear whether lineages of influenza A(H3N2) virus can persist in the tropics and seed temperate areas. We used viral gene sequence data sampled from Peru to test this source–sink model for a Latin American country. Viruses were obtained during 2010–2012 from influenza surveillance cohorts in Cusco, Tumbes, Puerto Maldonado, and Lima. Specimens positive for influenza A(H3N2) virus were randomly selected and underwent hemagglutinin sequencing and phylogeographic analyses. Analysis of 389 hemagglutinin sequences from Peru and 2,192 global sequences demonstrated interseasonal extinction of Peruvian lineages. Extensive mixing occurred with global clades, but some spatial structure was observed at all sites; this structure was weakest in Lima and Puerto Maldonado, indicating that these locations may experience greater viral traffic. The broad diversity and co-circulation of many simultaneous lineages of H3N2 virus in Peru suggests that this country should not be overlooked as a potential source for novel pandemic strains.

Protothecosis is a rare algal infection, affecting primarily immunocompromised hosts. Optimal management is unclear: in-vitro antimicrobial breakpoints are not established and therapeutic decisions are primarily based on case reports. We present a case of cutaneous Prototheca wickerhamii infection in an immunosuppressed 63 year old male, successfully treated with liposomal amphotericin and prolonged itraconazole. Inoculation may have been through frequent hot-tub use, highlighting hot-tub exposure as an infection risk for the immunocompromised host.

Internet-based surveillance methods for vector-borne diseases (VBDs) using "big data" sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such "digital disease detection" methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of "digital epidemiology." We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD.

Our understanding of the global ecology of avian influenza A viruses (AIVs) is impeded by historically low levels of viral surveillance in Latin America. Through sampling and whole-genome sequencing of 31 AIVs from wild birds in Peru, we identified 10 HA subtypes (H1-H4, H6-H7, H10-H13) and 8 NA subtypes (N1-N3, N5-N9). The majority of Peruvian AIVs were closely related to AIVs found in North America. However, unusual reassortants, including a H13 virus containing a PA segment related to extremely divergent Argentinian viruses, suggest that substantial AIV diversity circulates undetected throughout South America.

OBJECTIVES:Extra-pulmonary tuberculosis (EPTB) is relatively neglected and increasing in incidence, in comparison to pulmonary tuberculosis (PTB) in low-burden settings. It poses particular diagnostic and management challenges. We aimed to determine the characteristics of EPTB in Western Sydney, Australia, and to conduct a quality assurance investigation of adherence to guidelines among Infectious Diseases (ID) practitioners managing EPTB cases. METHODS:All adult EPTB cases managed by a large ID service during 01/01/2008-31/12/2011 were eligible for inclusion in the retrospective review. Data were extracted from patient medical records on demographic, diagnostic, clinical and management details, and on clinician adherence to local and international TB guidelines. RESULTS:129 cases managed by the ID service were identified, with files available for 117. 98 cases were managed by the Respiratory service and were excluded. 98.2%(112/114) had been born in a country other than Australia. HIV status was tested or previously known in 97 people, and positive in 4 (4%). Microbiological confirmation was obtained in 68/117 (58.1%), an additional 24 had histopathological findings considered confirmatory (92/117, 78.6%), with the remainder diagnosed on clinical and/or radiological grounds. Median time to diagnosis post-migration from a high TB-burden country was 5 years (range 0-41). 95 cases were successfully treated, 11 cases defaulted, refused therapy or transferred, 2 cases relapsed and outcomes unknown or pending in 9 cases. No deaths occurred in the sample analysed. Clinician adherence to guidelines was high, but with scope for improvement in offering testing for co-infections, performing eye checks, monitoring blood glucose in patients receiving adjunctive corticosteroids, and considering drug interactions. CONCLUSIONS:Despite excellent TB outcomes in this setting, the low proportion of cases with susceptibility data is worrying in this era of increasing drug resistance, and illustrates the diagnostic difficulties faced even in a well-resourced setting. Vigilance for EPTB needs to remain high in those moving from high prevalence countries to Australia, even decades after immigration.