Background: Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total population data. Methods: Total population data on age, tribe, religion, socioeconomic status, sexual activity, and HIV status were available on a population of 2402 male household heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, using current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample). Results: We recruited 927 household heads. Full and small RDS samples were largely representative of the total population, but both samples underrepresented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven sampling statistical inference methods failed to reduce these biases. Only 31%–37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%–74% of respondent-driven sampling bootstrap 95% confidence intervals included the population proportion. Conclusions: Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience sampling method, and caution is required when interpreting findings based on the sampling method.

Patterns of social mixing are key determinants of epidemic spread. Here we present the results of an internet-based social contact survey completed by a cohort of participants over 9,000 times between July 2009 and March 2010, during the 2009 H1N1v influenza epidemic. We quantify the changes in social contact patterns over time, finding that school children make 40% fewer contacts during holiday periods than during term time. We use these dynamically varying contact patterns to parameterise an age-structured model of influenza spread, capturing well the observed patterns of incidence; the changing contact patterns resulted in a fall of approximately 35% in the reproduction number of influenza during the holidays. This work illustrates the importance of including changing mixing patterns in epidemic models. We conclude that changes in contact patterns explain changes in disease incidence, and that the timing of school terms drove the 2009 H1N1v epidemic in the UK. Changes in social mixing patterns can be usefully measured through simple internet-based surveys. Changes in patterns of social mixing can result in changes in epidemic behaviour; this was observed during the 2009 influenza pandemic, in which the epidemic declined during school holidays and grew during term time. Until now, little information has been available to quantify how people's mixing patterns change over time. Here, we present the results of an internet-based survey of social mixing patterns that was carried out in the UK throughout the 2009 pandemic. We show that school holidays resulted in a substantial drop in the number of social contacts made each day, particularly between children. To test whether these measured patterns of social mixing could explain the observed epidemic, we used our mixing data in a simple mathematical model of influenza spread. We found that changing social contact behaviour could explain levels of infection in the community, and conclude that the timing of school terms was responsible for the shape of the influenza epidemic.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), emerged at the end of 2019 and by mid-June 2020 the virus had spread to at least 215 countries, caused more than 8 000 000 confirmed infections and over 450 000 deaths, and overwhelmed healthcare systems worldwide. Like severe acute respiratory syndrome coronavirus (SARS-CoV), which emerged in 2002 and caused a similar disease, SARS-CoV-2 is a betacoronavirus. Both viruses use human angiotensin-converting enzyme 2 (hACE2) as a receptor to enter cells. However, the SARS-CoV-2 spike (S) glycoprotein has a novel insertion that generates a putative furin cleavage signal and this has been postulated to expand the host range. Two low-passage (P) strains of SARS-CoV-2 (Wash1 : P4 and Munich : P1) were cultured twice in Vero E6 cells and characterized virologically. Sanger and MinION sequencing demonstrated significant deletions in the furin cleavage signal of Wash1 : P6 and minor variants in the Munich : P3 strain. Cleavage of the S glycoprotein in SARS-CoV-2-infected Vero E6 cell lysates was inefficient even when an intact furin cleavage signal was present. Indirect immunofluorescence demonstrated that the S glycoprotein reached the cell surface. Since the S protein is a major antigenic target for the development of neutralizing antibodies, we investigated the development of neutralizing antibody titres in serial serum samples obtained from COVID-19 human patients. These were comparable regardless of the presence of an intact or deleted furin cleavage signal. These studies illustrate the need to characterize virus stocks meticulously prior to performing either in vitro or in vivo pathogenesis studies.

Vaccines are urgently needed to combat the global coronavirus disease 2019 (COVID-19) pandemic, and testing of candidate vaccines in an appropriate non-human primate (NHP) model is a critical step in the process. Infection of African green monkeys (AGM) with a low passage human isolate of SARS-CoV-2 by aerosol or mucosal exposure resulted in mild clinical infection with a transient decrease in lung tidal volume. Imaging with human clinical-grade ¹⁸F-fluoro-2-deoxy-D-glucose positron emission tomography (¹⁸F-FDG PET) co-registered with computed tomography (CT) revealed pulmonary lesions at 4 days post-infection (dpi) that resolved over time. Infectious virus was shed from both respiratory and gastrointestinal (GI) tracts in all animals in a biphasic manner, first between 2–7 dpi followed by a recrudescence at 14–21 dpi. Viral RNA (vRNA) was found throughout both respiratory and gastrointestinal systems at necropsy with higher levels of vRNA found within the GI tract tissues. All animals seroconverted simultaneously for IgM and IgG, which has also been documented in human COVID-19 cases. Young AGM represent an species to study mild/subclinical COVID-19 disease and with possible insights into live virus shedding. Future vaccine evaluation can be performed in AGM with correlates of efficacy being lung lesions by PET/CT, virus shedding, and tissue viral load. SARS-CoV-2 infection can result in asymptomatic, mild or severe disease in humans. Vaccines against SARS-CoV-2 are paramount for combating COVID-19 disease and curtailing the pandemic. Large animal models are critical for early vaccine testing before human clinical trials. Here, we found that infection of African green monkeys (AGM) with SARS-CoV-2 resulted in mild disease yet lesions were detectable by PET/CT imaging of the lungs. Shedding of infectious virus from both respiratory and gastrointestinal tracts was also documented. This study provides a detailed account of the pathogenesis of a low-passage SARS-CoV-2 isolate in the AGM model and suggests that AGM can be used for preclinical evaluation of candidate vaccines and therapeutic interventions.

Oropouche virus (OROV) is a midge-borne human pathogen with a geographic distribution in South America. OROV was first isolated in 1955, and since then, it has been known to cause recurring outbreaks of a dengue-like illness in the Amazonian regions of Brazil. OROV, however, remains one of the most poorly understood emerging viral zoonoses. Here we describe the successful recovery of infectious OROV entirely from cDNA copies of its genome and generation of OROV mutant viruses lacking either the NSm or the NSs coding region. Characterization of the recombinant viruses carried out in vitro demonstrated that the NSs protein of OROV is an interferon (IFN) antagonist as in other NSs-encoding bunyaviruses. Additionally, we demonstrate the importance of the nine C-terminal amino acids of OROV NSs in IFN antagonistic activity. OROV was also found to be sensitive to IFN-α when cells were pretreated; however, the virus was still capable of replicating at doses as high as 10,000 U/ml of IFN-α, in contrast to the family prototype BUNV. We found that OROV lacking the NSm protein displayed characteristics similar to those of the wild-type virus, suggesting that the NSm protein is dispensable for virus replication in the mammalian and mosquito cell lines that were tested. IMPORTANCE Oropouche virus (OROV) is a public health threat in Central and South America, where it causes periodic outbreaks of dengue-like illness. In Brazil, OROV is the second most frequent cause of arboviral febrile illness after dengue virus, and with the current rates of urban expansion, more cases of this emerging viral zoonosis could occur. To better understand the molecular biology of OROV, we have successfully rescued the virus along with mutants. We have established that the C terminus of the NSs protein is important in interferon antagonism and that the NSm protein is dispensable for virus replication in cell culture. The tools described in this paper are important in terms of understanding this important yet neglected human pathogen.