Duration Of Infectiousness Research Articles

Phenotypic evolution of SARS-CoV-2: a statistical inference approach.

Since its emergence in late 2019, the SARS-CoV-2 virus has spread globally, causing the ongoing COVID-19 pandemic. In the fall of 2020, the Alpha variant (lineage B.1.1.7) was detected in England and spread rapidly, outcompeting the previous lineage. Yet, very little is known about the underlying modifications of the infection process that can explain this selective advantage. Here, we try to quantify how the Alpha variant differed from its predecessor on two phenotypic traits: the transmission rate and the duration of infectiousness. To this end, we analysed the joint epidemiological and evolutionary dynamics as a function of the Stringency Index, a measure of the amount of Non-Pharmaceutical Interventions. Assuming that these control measures reduce contact rates and transmission, we developed a two-step approach based on SEIR models and the analysis of a combination of epidemiological and evolutionary information. First, we quantify the link between the Stringency Index and the reduction in viral transmission. Secondly, based on a novel theoretical derivation of the selection gradient in an SEIR model, we infer the phenotype of the Alpha variant from its frequency changes. We show that its selective advantage is more likely to result from a higher transmission than from a longer infectious period. Our work illustrates how the analysis of the joint epidemiological and evolutionary dynamics of infectious diseases can help understand the phenotypic evolution driving pathogen adaptation.

Comparing the transmission potential from sequence and surveillance data of 2009 North American influenza pandemic waves.

Technological advancements in phylodynamic modeling coupled with the accessibility of real-time pathogen genetic data are increasingly important for understanding the infectious disease transmission dynamics. In this study, we compare the transmission potentials of North American influenza A(H1N1)pdm09 derived from sequence data to that derived from surveillance data. The impact of the choice of tree-priors, informative epidemiological priors, and evolutionary parameters on the transmission potential estimation is evaluated. North American Influenza A(H1N1)pdm09 hemagglutinin (HA) gene sequences are analyzed using the coalescent and birth-death tree prior models to estimate the basic reproduction number (R 0 ). Epidemiological priors gathered from published literature are used to simulate the birth-death skyline models. Path-sampling marginal likelihood estimation is conducted to assess model fit. A bibliographic search to gather surveillance-based R 0 values were consistently lower (mean≤1.2) when estimated by coalescent models than by the birth-death models with informative priors on the duration of infectiousness (mean≥1.3 to ≤2.88 days). The user-defined informative priors for use in the birth-death model shift the directionality of epidemiological and evolutionary parameters compared to non-informative estimates. While there was no certain impact of clock rate and tree height on the R 0 estimation, an opposite relationship was observed between coalescent and birth-death tree priors. There was no significant difference (p=0.46) between the birth-death model and surveillance R 0 estimates. This study concludes that tree-prior methodological differences may have a substantial impact on the transmission potential estimation as well as the evolutionary parameters. The study also reports a consensus between the sequence-based R 0 estimation and surveillance-based R 0 estimates. Altogether, these outcomes shed light on the potential role of phylodynamic modeling to augment existing surveillance and epidemiological activities to better assess and respond to emerging infectious diseases.

Adherence to weekly anal self-examination among men who have sex with men for detection of anal syphilis.

BackgroundMen who have sex with men (MSM) practicing exclusively receptive anal sex are more likely to present with secondary than primary syphilis, implying primary anorectal lesions may be missed. If men could detect anorectal lesions by regular anal self-examination, the duration of infectiousness could be reduced. This study aimed to examine adherence to weekly anal self-examination.MethodWe conducted a longitudinal feasibility study examining the adherence to weekly anal self-examinations among MSM attending a sexual health clinic in Melbourne, Australia between December 2020 and June 2021. Adherence to weekly anal self-examinations over 12 weeks was assessed from a logbook and 4-weekly surveys. Participants who identified abnormalities in their anus were recommended to seek medical review.ResultsOf the 30 men who completed the study, anal self-examination was performed at least weekly for 308 of 360 person-weeks (86% of the weeks, 95% CI: 82–89). The mean adherence was 3.6 (95% CI: 3.3–3.9) examinations per 4-weeks per person in Weeks 1–4, 3.5 (95% CI: 3.1–3.8) in Weeks 5–8 and 3.3 (95% CI: 2.9–3.7) in Weeks 9–12 (Ptrend = 0.06). Six men (20%, 6/30) were seen for medical review after they identified abnormalities, whilst eight men (27%, 8/30) reported abnormalities, but did not seek medical review. No participants were diagnosed with syphilis during the study period.ConclusionWe conclude that men adhered well to weekly anal self-examination. Therefore, it is feasible to trial this as a routine practice among MSM. Future studies should investigate possible reductions in adherence over time and ways to increase medical review for abnormalities that men find.

Clinical, Subclinical Characteristics, Treatment Results of COVID-19 patients in Dong Thap

A prospective descriptive study was conducted from August 2021 to September 2021 to describe the clinical and subclinical characteristics of COVID-19 patients at the field hospital of Dong Thap Community College. The study collected epidemiological data of 240 subjects. The results indicated that the male/female ratio was 1.2/1; the mean age was 29.2±15.1 (1- 65 years old). The most typical clinical symptoms of the disease are cough (45.8%), fever (45%), stuffy nose (21.7%), anosmia (13.8%), ageusia (12.9%), and shortness of breath (4.6%). Most patients have mild symptoms and a high recovery rate. This study contributes to a general assessment of clinical, subclinical factors, treatment results of COVID-19 patients in general and COVID-19 subjects at the field hospital of Dong Thap Community College in particular, which is the basis for better disease prevention measures.
 Keywords: COVID-19, clinical features, Ct index, treatment results.
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Persistence of live virus in critically ill patients infected with SARS-COV-2: a prospective observational study

BackgroundResearch on the duration of infectivity of ICU patients with COVID-19 has been sparse. Tests based on Reverse Transcriptase polymerase chain reaction (RT-PCR) detect both live virus and non-infectious viral RNA. We aimed to determine the duration of infectiousness based on viral culture of nasopharyngeal samples of patients with COVID-19.MethodsProspective observational study in adult intensive care units with a diagnosis of COVID-19 Pneumonia. Patients had repeated nasopharyngeal sampling performed after day 10 of ICU admission. Culture positive rate (based on viral culture on Vero cells in a level 4 lab) and Cycle threshold from RT-PCR were measured.ResultsNine patients of the 108 samples (8.3%, 95% CI 3.9–15.2%) grew live virus at a median of 13 days (interquartile range 11–19) after their initial positive test. 74.1% of patients were RT-PCR positive but culture negative, and the remaining (17.6%) were RT-PCR and culture negative. Cycle threshold showed excellent ability to predict the presence of live virus, with a Ct < 25 with an AUC of 0.90 (95% CI 0.83–0.97, p < 0.001). The specificity of a Ct > 25 to predict negative viral culture was 100% (95% CI 70–100%).Conclusion8.3% of our ICU patients with COVID-19 grew live virus at a median of 13 days post-initial positive RT-PCR test. Severity of illness, use of mechanical ventilation, and time between tests did not predict the presence of live virus. Cycle threshold of > 25 had the best ability to determine the lack of live virus in these patents.

Time-varying sensitivity analysis of an influenza model with interventions

We formulate an influenza model with treatment and vaccination. Both time invariant and time-dependent uncertainty analyses and sensitivity analysis of the model parameter values are carried out to understand the dependence of the reproduction numbers and model state variables on their components. Results show that the relationship between treatment and epidemic size is nonlinear and that there exists a critical threshold treatment rate under which treatment is beneficial. Sensitivity analysis suggests that the most significant parameters are those related to infection transmission, infectiousness, duration of infectiousness and waning immunity. Further, there are important instances when the relationship between some parameters and model outputs changes behavior from negatively to positively correlated or vice versa because all sensitivity indices, except [Formula: see text] are functions of other parameters and thus will change with the change in parameter values. For example, treatment helps to lower the epidemic size, but may then become a “source” of infection likely due to resistance de novo. This knowledge is critical for proper public health planning and guidance of control strategies.

Superspreading of airborne pathogens in a heterogeneous world

Epidemics are regularly associated with reports of superspreading: single individuals infecting many others. How do we determine if such events are due to people inherently being biological superspreaders or simply due to random chance? We present an analytically solvable model for airborne diseases which reveal the spreading statistics of epidemics in socio-spatial heterogeneous spaces and provide a baseline to which data may be compared. In contrast to classical SIR models, we explicitly model social events where airborne pathogen transmission allows a single individual to infect many simultaneously, a key feature that generates distinctive output statistics. We find that diseases that have a short duration of high infectiousness can give extreme statistics such as 20% infecting more than 80%, depending on the socio-spatial heterogeneity. Quantifying this by a distribution over sizes of social gatherings, tracking data of social proximity for university students suggest that this can be a approximated by a power law. Finally, we study mitigation efforts applied to our model. We find that the effect of banning large gatherings works equally well for diseases with any duration of infectiousness, but depends strongly on socio-spatial heterogeneity.

Improving the Outcomes of Immunocompromised Patients With Coronavirus Disease 2019.

Recent case studies have highlighted the fact that certain immunocompromised individuals are at risk for prolonged SARS-CoV-2 replication, intrahost viral evolution of multiply-mutated variants, and poor clinical outcomes. The immunologic determinants of this risk, the duration of infectiousness, and optimal treatment and prevention strategies in immunocompromised hosts are ill defined. Of additional concern is the widespread use of immunosuppressive medications to treat COVID-19, which may enhance and prolong viral replication in the context of immunodeficiency. We outline the rationale for 4 interrelated approaches to usher in an era of evidence-based medicine for optimal management of immunocompromised patients with COVID-19: multicenter pathogenesis and outcomes studies to relate the risk of severe disease to the type and degree of immunodeficiency, studies to evaluate immunologic responses to SARS-CoV-2 vaccines, studies to evaluate the efficacy of monoclonal antibodies for primary prophylaxis, and clinical trials of novel antiviral agents for the treatment of COVID-19.

Population density and basic reproductive number of COVID-19 across United States counties.

The basic reproductive number (R0) is a function of contact rates among individuals, transmission probability, and duration of infectiousness. We sought to determine the association between population density and R0 of SARS-CoV-2 across U.S. counties. We conducted a cross-sectional analysis using linear mixed models with random intercept and fixed slopes to assess the association of population density and R0, and controlled for state-level effects using random intercepts. We also assessed whether the association was differential across county-level main mode of transportation percentage as a proxy for transportation accessibility, and adjusted for median household income. The median R0 among the United States counties was 1.66 (IQR: 1.35-2.11). A population density threshold of 22 people/km2 was needed to sustain an outbreak. Counties with greater population density have greater rates of transmission of SARS-CoV-2, likely due to increased contact rates in areas with greater density. An increase in one unit of log population density increased R0 by 0.16 (95% CI: 0.13 to 0.19). This association remained when adjusted for main mode of transportation and household income. The effect of population density on R0 was not modified by transportation mode. Our findings suggest that dense areas increase contact rates necessary for disease transmission. SARS-CoV-2 R0 estimates need to consider this geographic variability for proper planning and resource allocation, particularly as epidemics newly emerge and old outbreaks resurge.

Characteristics of Viral Shedding Time in SARS-CoV-2 Infections: A Systematic Review and Meta-Analysis.

Background: The viral shedding time (VST) of SARS-CoV-2 mainly determines its transmission and duration of infectiousness. However, it was heterogeneous in the existing studies. Here, we performed a meta-analysis to comprehensively summarize the VST of SARS-CoV-2.Methods: We searched PubMed, Web of Science, MedRxiv, BioRxiv, CNKI, CSTJ, and Wanfang up to October 25, 2020, for studies that reported VSTs of SARS-CoV-2. Pooled estimates and 95% CIs for the VSTs were calculated using log-transformed data. The VSTs in SARS-CoV-2 infections based on different demographic and clinical characteristics, treatments and specimens were stratified by subgroup analysis.Results: A total of 35 studies involving 3,385 participants met the inclusion criteria. The pooled mean VST was 16.8 days (95% CI: 14.8–19.4, I2 = 99.56%) in SARS-CoV-2 infections. The VST was significantly longer in symptomatic infections (19.7 days, 95% CI: 17.2–22.7, I2 = 99.34%) than in asymptomatic infections (10.9 days, 95% CI: 8.3–14.3, I2 = 98.89%) (P < 0.05). The VST was 23.2 days (95% CI: 19.0–28.4, I2 = 99.24%) in adults, which was significantly longer than that in children (9.9 days, 95% CI: 8.1–12.2, I2 = 85.74%) (P < 0.05). The VST was significantly longer in persons with chronic diseases (24.2 days, 95% CI: 19.2–30.2, I2 = 84.07%) than in those without chronic diseases (11.5 days, 95% CI: 5.3–25.0, I2 = 82.11%) (P < 0.05). Persons receiving corticosteroid treatment (28.3 days, 95% CI: 25.6–31.2, I2 = 0.00%) had a longer VST than those without corticosteroid treatment (16.2 days, 95% CI: 11.5–22.5, I2 = 92.27%) (P = 0.06). The VST was significantly longer in stool specimens (30.3 days, 95% CI: 23.1–39.2, I2 = 92.09%) than in respiratory tract specimens (17.5 days, 95% CI: 14.9–20.6, I2 = 99.67%) (P < 0.05).Conclusions: A longer VST was found in symptomatic infections, infected adults, persons with chronic diseases, and stool specimens.

Characterization of potential superspreader farms for bovine tuberculosis: A review.

BackgroundVariation in host attributes that influence their contact rates and infectiousness can lead some individuals to make disproportionate contributions to the spread of infections. Understanding the roles of such ‘superspreaders’ can be crucial in deciding where to direct disease surveillance and controls to greatest effect. In the epidemiology of bovine tuberculosis (bTB) in Great Britain, it has been suggested that a minority of cattle farms or herds might make disproportionate contributions to the spread of Mycobacterium bovis, and hence might be considered ‘superspreader farms’.Objectives and MethodsWe review the literature to identify the characteristics of farms that have the potential to contribute to exceptional values in the three main components of the farm reproductive number ‐ Rf: contact rate, infectiousness and duration of infectiousness, and therefore might characterize potential superspreader farms for bovine tuberculosis in Great Britain.ResultsFarms exhibit marked heterogeneity in contact rates arising from between‐farm trading of cattle. A minority of farms act as trading hubs that greatly augment connections within cattle trading networks. Herd infectiousness might be increased by high within‐herd transmission or the presence of supershedding individuals, or infectiousness might be prolonged due to undetected infections or by repeated local transmission, via wildlife or fomites.ConclusionsTargeting control methods on putative superspreader farms might yield disproportionate benefits in controlling endemic bovine tuberculosis in Great Britain. However, real‐time identification of any such farms, and integration of controls with industry practices, present analytical, operational and policy challenges.

Duration of infectiousness and correlation with RT-PCR cycle threshold values in cases of COVID-19, England, January to May 2020.

Severe acute respiratory syndrome coronavirus 2 viral load in the upper respiratory tract peaks around symptom onset and infectious virus persists for 10 days in mild-to-moderate coronavirus disease (n = 324 samples analysed). RT-PCR cycle threshold (Ct) values correlate strongly with cultivable virus. Probability of culturing virus declines to 8% in samples with Ct > 35 and to 6% 10 days after onset; it is similar in asymptomatic and symptomatic persons. Asymptomatic persons represent a source of transmissible virus.

The Effect Of Social Contacts On The Spreads Of Covid-19 In Indonesia

Introduction: Covid-19 is an infectious disease. Matrix that is often used to identify transmission of infectious diseases dynamics is Basic Reproduction Number (R0). R0 is influenced by 3 parameters there are transmissibility (τ), average contact (c) and duration of infectiousness (d). Transmissibility and duration of infectiousness are constant values. The value of R0 will fluctuate if the rate of human interaction varies. The value of social contact different in every country. In Indonesia, there are no studies that discuss the value of social contact. Therefore researchers aims to find out these values and determine their effect on the spread of Covid-19.&#x0D; Method: This research was a descriptive observational study. Aims of the study is evaluate the pattern of social contact associated with the spread of covid-19. Data was collected using POLYMOD questionnaire that distributed via google form. The research sample was Indonesian people who were reached by distributing questionnaires. The data obtained then analyzed using the SPSS program to find the frequency distribution, mean of social contact and logistic regression analysis.&#x0D; Results: From this study, 6464 contacts were obtained from 1032 respondents with average number of contacts 6.26 and R0 2.191.&#x0D; Conclusion: The higher of contact value the higher risk of transmission. The R0 value obtained is 2.191, so one infected person might be able to transmit it to two other people around them. Individuals who are most at risk for transmission is male with low education levels and students.

The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study

SummaryBackgroundIn December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world.MethodsTo examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April).FindingsOur projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66–97) and 24% (13–90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic.InterpretationRestrictions on activities in Wuhan, if maintained until April, would probably help to delay the epidemic peak. Our projections suggest that premature and sudden lifting of interventions could lead to an earlier secondary peak, which could be flattened by relaxing the interventions gradually. However, there are limitations to our analysis, including large uncertainties around estimates of R0 and the duration of infectiousness.FundingBill & Melinda Gates Foundation, National Institute for Health Research, Wellcome Trust, and Health Data Research UK.

The Effect of Control Strategies that Reduce Social Mixing on Outcomes of the COVID-19 Epidemic in Wuhan, China

Background: In December 2019, a novel strain of SARS-CoV-2 emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures and efforts in response to the outbreak. Methods: We quantified the effects of control measures on population contact patterns in Wuhan, China, to assess their effects on the progression of the outbreak. We included the latest estimates of epidemic parameters from a transmission model fitted to data on local and internationally exported cases from Wuhan in the age-structured epidemic framework. Further, we looked at the age-distribution of cases. Lastly, we simulated lifting of the control measures by allowing people to return to work in a phased-in way, and looked at the effects of returning to work at different stages of the underlying outbreak. Findings: Changes in mixing patterns may have contributed to reducing the number of infections in mid-2020 by 92% (interquartile range: 66–97%). There are benefits to sustaining these measures until April in terms of reducing the height of the peak, overall epidemic size in mid-2020 and probability that a second peak may occur after return to work. However, the modelled effects of social distancing measures vary by the duration of infectiousness and the role school children play in the epidemic. Interpretation: Restrictions on activities in Wuhan, if maintained until April, would likely contribute to the reduction and delay the epidemic size and peak, respectively. However, there are some limitations to the analysis, including large uncertainties around estimates of R0 and the duration of infectiousness.Funding: KP, YL, MJ, and PK were funded by the Bill & Melinda Gates Foundation (grant number INV003174), YL and MJ were funded by the National Institute for Health Research (NIHR) (16/137/109), TWR and AJK were funded by the Wellcome Trust (grant number 206250/Z/17/Z), RME was funded by HDR UK (grant number MR/S003975/1), and ND was funded by NIHR (HPRU-2012-10096).This research was partly funded by the National Institute for Health Research (NIHR) (16/137/109) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. We would like to acknowledge (in a randomised order) the other members of the London School of Hygiene & Tropical Medicine COVID-19 modelling group, who contributed to this work: Stefan Flasche, Samuel Clifford, Carl A B Pearson, James D Munday, Sam Abbott, Hamish Gibbs, Alicia Rosello, Billy J Quilty, Thibaut Jombart, Fiona Sun, Charlie Diamond, Amy Gimma, Kevin van Zandvoort, Sebastian Funk, Christopher I Jarvis, W John Edmunds, Nikos I Bosse, and Joel Hellewell. Their funding sources are as follows: Stefan Flasche and Sam Clifford (Sir Henry Dale Fellowship [grant number 208812/Z/17/Z]); Billy J Quilty, Fiona Sun, and Charlie Diamond (NIHR [grant number 16/137/109]); Joel Hellewell, Sam Abbott, James D Munday, and Sebastian Funk (Wellcome Trust [grant number 210758/Z/18/Z] ); Amy Gimma and Christopher I Jarvis (Global Challenges Research Fund [grant number ES/P010873/1]); Hamish Gibbs (Department of Health and Social Care [grant number ITCRZ 03010]); Alicia Rosello (NIHR [grant number PROD-1017-20002]); Thibaut Jombart (RCUK/ESRC [grant number ES/P010873/1], UK PH RST, NIHR HPRU Modelling Methodology); Kevin van Zandvoort (Elrha’s Research for Health in Humanitarian Crises (R2HC) Programme, UK Government (DFID), Wellcome Trust, NIHR).Declaration of Interest: The authors declare no competing interests.

Assessing the potential of plains zebra to maintain African horse sickness in the Western Cape Province, South Africa.

African horse sickness (AHS) is a disease of equids that results in a non-tariff barrier to the trade of live equids from affected countries. AHS is endemic in South Africa except for a controlled area in the Western Cape Province (WCP) where sporadic outbreaks have occurred in the past 2 decades. There is potential that the presence of zebra populations, thought to be the natural reservoir hosts for AHS, in the WCP could maintain AHS virus circulation in the area and act as a year-round source of infection for horses. However, it remains unclear whether the epidemiology or the ecological conditions present in the WCP would enable persistent circulation of AHS in the local zebra populations. Here we developed a hybrid deterministic-stochastic vector-host compartmental model of AHS transmission in plains zebra (Equus quagga), where host populations are age- and sex-structured and for which population and AHS transmission dynamics are modulated by rainfall and temperature conditions. Using this model, we showed that populations of plains zebra present in the WCP are not sufficiently large for AHS introduction events to become endemic and that coastal populations of zebra need to be >2500 individuals for AHS to persist >2 years, even if zebras are infectious for more than 50 days. AHS cannot become endemic in the coastal population of the WCP unless the zebra population involves at least 50,000 individuals. Finally, inland populations of plains zebra in the WCP may represent a risk for AHS to persist but would require populations of at least 500 zebras or show unrealistic duration of infectiousness for AHS introduction events to become endemic. Our results provide evidence that the risk of AHS persistence from a single introduction event in a given plains zebra population in the WCP is extremely low and it is unlikely to represent a long-term source of infection for local horses.

Parameterization of the Durations of Phases of Foot-And-Mouth Disease in Cattle.

The objective of the current study was to update parameterization of mathematical simulation models for foot-and-mouth disease (FMD) spread in cattle utilizing recent knowledge of FMD virus (FMDV) pathogenesis and infection dynamics to estimate the duration of distinct phases of FMD. Specifically, the durations of incubation, latent, and infectious periods were estimated for 3 serotypes (O, Asia1, and A) of FMDV, individually and collectively (pan-serotypic). Animal-level data were used in Accelerated Failure Time (AFT) models to estimate the duration of the defined phases of infection, while also investigating the influence of factors related to the experimental design (exposure methods) and virus serotype on disease progression. Substantial influences upon the estimated duration of distinct phases of FMD included the quantity of viral shedding used as a proxy for the onset of infectiousness, virus serotypes, and experimental exposure methods. The use of detection of any viral RNA in nasal secretions as a proxy of infectiousness lengthened the total infectious period compared to use of threshold-based detection. Additionally, the experimental system used to infect the animals also had significant effects on the duration of distinct phases of disease. Overall, the mean [95% Confidence Interval (CI)] durations of pan-serotype disease phases in cattle were estimated to be: incubation phase = 3.6 days (2.7–4.8), latent phase = 1.5 days (1.1–2.1), subclinical infectious phase = 2.2 days (1.5–3.5), clinical infectious phase = 8.5 days (6.2–11.6), and total infectious phase = 10.8 days (8.2–14.2). This study highlights the importance of identifying appropriate proxy measures to define the onset and duration of infectiousness in FMDV-infected cattle in the absence of actual transmission data. Additionally, it is demonstrated herein that factors associated with experimental design, such as virus exposure methods, may significantly affect disease progression in individual animals and should be considered when data is extrapolated from experimental studies. Given limitations in experimental data availability, pan-serotypic parameters which include all routes of exposure and a threshold-defined onset of infectiousness may be the most robust parameters for exploratory disease spread modeling approaches, when information on the specific virus of interest is not available.

Sexual transmission of Zika virus and other flaviviruses: A living systematic review.

BackgroundHealth authorities in the United States and Europe reported an increasing number of travel-associated episodes of sexual transmission of Zika virus (ZIKV) following the 2015–2017 ZIKV outbreak. This, and other scientific evidence, suggests that ZIKV is sexually transmissible in addition to having its primary mosquito-borne route. The objective of this systematic review and evidence synthesis was to clarify the epidemiology of sexually transmitted ZIKV.Methods and findingsWe performed a living (i.e., continually updated) systematic review of evidence published up to 15 April 2018 about sexual transmission of ZIKV and other arthropod-borne flaviviruses in humans and other animals. We defined 7 key elements of ZIKV sexual transmission for which we extracted data: (1) rectal and vaginal susceptibility to infection, (2) incubation period following sexual transmission, (3) serial interval between the onset of symptoms in a primary and secondary infected individuals, (4) duration of infectiousness, (5) reproduction number, (6) probability of transmission per sex act, and (7) transmission rate. We identified 1,227 unique publications and included 128, of which 77 presented data on humans and 51 presented data on animals. Laboratory experiments confirm that rectal and vaginal mucosae are susceptible to infection with ZIKV and that the testis serves as a reservoir for the virus in animal models. Sexual transmission was reported in 36 human couples: 34/36 of these involved male-to-female sexual transmission. The median serial symptom onset interval in 15 couples was 12 days (interquartile range: 10–14.5); the maximum was 44 days. We found evidence from 2 prospective cohorts that ZIKV RNA is present in human semen with a median duration of 34 days (95% CI: 28–41 days) and 35 days (no CI given) (low certainty of evidence, according to GRADE). Aggregated data about detection of ZIKV RNA from 37 case reports and case series indicate a median duration of detection of ZIKV of 40 days (95% CI: 30–49 days) and maximum duration of 370 days in semen. In human vaginal fluid, median duration was 14 days (95% CI: 7–20 days) and maximum duration was 37 days (very low certainty). Infectious virus in human semen was detected for a median duration of 12 days (95% CI: 1–21 days) and maximum of 69 days. Modelling studies indicate that the reproduction number is below 1 (very low certainty). Evidence was lacking to estimate the incubation period or the transmission rate. Evidence on sexual transmission of other flaviviruses was scarce. The certainty of the evidence is limited because of uncontrolled residual bias.ConclusionsThe living systematic review and sexual transmission framework allowed us to assess evidence about the risk of sexual transmission of ZIKV. ZIKV is more likely transmitted from men to women than from women to men. For other flaviviruses, evidence of sexual transmissibility is still absent. Taking into account all available data about the duration of detection of ZIKV in culture and from the serial interval, our findings suggest that the infectious period for sexual transmission of ZIKV is shorter than estimates from the earliest post-outbreak studies, which were based on reverse transcription PCR alone.

Structural and Practical Identifiability Analysis of Zika Epidemiological Models.

The Zika virus (ZIKV) epidemic has caused an ongoing threat to global health security and spurred new investigations of the virus. Use of epidemiological models for arbovirus diseases can be a powerful tool to assist in prevention and control of the emerging disease. In this article, we introduce six models of ZIKV, beginning with a general vector-borne model and gradually including different transmission routes of ZIKV. These epidemiological models use various combinations of disease transmission (vector and direct) and infectious classes (asymptomatic and pregnant), with addition to loss of immunity being included. The disease-induced death rate is omitted from the models. We test the structural and practical identifiability of the models to find whether unknown model parameters can uniquely be determined. The models were fit to obtain time-series data of cumulative incidences and pregnant infections from the Florida Department of Health Daily Zika Update Reports. The average relative estimation errors (AREs) were computed from the Monte Carlo simulations to further analyze the identifiability of the models. We show that direct transmission rates are not practically identifiable; however, fixed recovery rates improve identifiability overall. We found ARE is low for each model (only slightly higher for those that account for a pregnant class) and help to confirm a reproduction number greater than one at the start of the Florida epidemic. Basic reproduction number, [Formula: see text], is an epidemiologically important threshold value which gives the number of secondary cases generated by one infected individual in a totally susceptible population in duration of infectiousness. Elasticity of the reproduction numbers suggests that the mosquito-to-human ratio, mosquito life span and biting rate have the greatest potential for reducing the reproduction number of Zika, and therefore, corresponding control measures need to be focused on.

Time from HIV infection to virological suppression

Time from HIV infection to virological suppression: dramatic fall from 2007 to 2016. We examined the time from HIV infection to virological suppression in MSM who were first diagnosed at Melbourne Sexual Health Centre between 2007 and 2016. Retrospective cohort. Date of infection was imputed from the testing history or serological evidence of recent infection (negative or indeterminate western blot) or baseline CD4 cell count. Date of virological suppression was determined using clinical viral load data. We analysed predictors of diagnosis with serological evidence of recent infection (logistic regression) and time from diagnosis to suppression and from infection to suppression (Cox regression) using demographic, clinical, and behavioral covariates. Between 2007 and 2016, the median time from HIV infection to diagnosis fell from 6.8 to 4.3 months (P = 0.001), from diagnosis to suppression fell from 22.7 to 3.2 months (P < 0.0001), and from infection to suppression fell from 49.0 to 9.6 months (P < 0.0001). Serological evidence of recent infection increased from 15.6 to 34.3% (P < 0.0001) of diagnoses. In the multivariate analyses, age, being recently arrived from a non-English speaking country, history of IDU, other sexually transmitted infections, and sexual risk were not associated with any of these measures. The duration of infectiousness in MSM diagnosed with HIV infection at Melbourne Sexual Health Centre in Victoria has fallen dramatically between 2007 and 2016 and the proportion diagnosed with serological evidence of recent infection has increased. This effect is observed across all population subgroups and marks a positive milestone for the treatment as prevention paradigm.