Designing effective control of dengue with combined interventions

Viruses transmitted by Aedes mosquitoes, such as dengue, Zika, and chikungunya, have expanding ranges and seem unabated by current vector control programs. Effective control of these pathogens likely requires integrated approaches. We evaluated dengue management options in an endemic setting that combine novel vector control and vaccination using an agent-based model for Yucatán, Mexico, fit to 37 y of data. Our intervention models are informed by targeted indoor residual spraying (TIRS) experiments; trial outcomes and World Health Organization (WHO) testing guidance for the only licensed dengue vaccine, CYD-TDV; and preliminary results for in-development vaccines. We evaluated several implementation options, including varying coverage levels; staggered introductions; and a one-time, large-scale vaccination campaign. We found that CYD-TDV and TIRS interfere: while the combination outperforms either alone, performance is lower than estimated from their separate benefits. The conventional model hypothesized for in-development vaccines, however, performs synergistically with TIRS, amplifying effectiveness well beyond their independent impacts. If the preliminary performance by either of the in-development vaccines is upheld, a one-time, large-scale campaign followed by routine vaccination alongside aggressive new vector control could enable short-term elimination, with nearly all cases avoided for a decade despite continuous dengue reintroductions. If elimination is impracticable due to resource limitations, less ambitious implementations of this combination still produce amplified, longer-lasting effectiveness over single-approach interventions

COVID-19 length of hospital stay: a systematic review and data synthesis.

BACKGROUND: The COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care. METHODS: We performed a systematic review of early evidence on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach, we provide distributions for total hospital and ICU LoS from studies in China and elsewhere, for use by the community. RESULTS: We identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies-four each within and outside China-with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR 10-19) days for China, compared with 5 (IQR 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date. CONCLUSION: Patients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China

Heavy-tailed sexual contact networks and monkeypox epidemiology in the global outbreak, 2022

The outbreak of monkeypox across non-endemic regions confirmed in May 2022 shows epidemiological features distinct from previously imported outbreaks, most notably its observed growth and predominance amongst men who have sex with men (MSM). We use a transmission model fitted to empirical sexual partnership data to show that the heavy-tailed sexual partnership distribution, in which a handful of individuals have disproportionately many partners, can explain the sustained growth of monkeypox among MSM despite the absence of such patterns previously. We suggest that the basic reproduction number (R0) for monkeypox over the MSM sexual network may be substantially above 1, which poses challenges to outbreak containment. Ensuring support and tailored messaging to facilitate prevention and early detection among MSM with high numbers of partners is warranted

The long-term safety, public health impact, and cost-effectiveness of routine vaccination with a recombinant, live-attenuated dengue vaccine (Dengvaxia): a model comparison study

This is the final version of the article. Available from the publisher via the DOI in this record.Background: Large Phase III trials across Asia and Latin America have recently demonstrated the efficacy of a recombinant, live-attenuated dengue vaccine (Dengvaxia) over the first 25 mo following vaccination. Subsequent data collected in the longer-term follow-up phase, however, have raised concerns about a potential increase in hospitalization risk of subsequent dengue infections, in particular among young, dengue-naïve vaccinees. We here report predictions from eight independent modelling groups on the long-term safety, public health impact, and cost-effectiveness of routine vaccination with Dengvaxia in a range of transmission settings, as characterised by seroprevalence levels among 9-y-olds (SP9). These predictions were conducted for the World Health Organization to inform their recommendations on optimal use of this vaccine. Methods and Findings: The models adopted, with small variations, a parsimonious vaccine mode of action that was able to reproduce quantitative features of the observed trial data. The adopted mode of action assumed that vaccination, similarly to natural infection, induces transient, heterologous protection and, further, establishes a long-lasting immunogenic memory, which determines disease severity of subsequent infections. The default vaccination policy considered was routine vaccination of 9-y-old children in a three-dose schedule at 80% coverage. The outcomes examined were the impact of vaccination on infections, symptomatic dengue, hospitalised dengue, deaths, and cost-effectiveness over a 30-y postvaccination period. Case definitions were chosen in accordance with the Phase III trials. All models predicted that in settings with moderate to high dengue endemicity (SP9 ≥ 50%), the default vaccination policy would reduce the burden of dengue disease for the population by 6%–25% (all simulations: –3%–34%) and in high-transmission settings (SP9 ≥ 70%) by 13%–25% (all simulations: 10%– 34%). These endemicity levels are representative of the participating sites in both Phase III trials. In contrast, in settings with low transmission intensity (SP9 ≤ 30%), the models predicted that vaccination could lead to a substantial increase in hospitalisation because of dengue. Modelling reduced vaccine coverage or the addition of catch-up campaigns showed that the impact of vaccination scaled approximately linearly with the number of people vaccinated. In assessing the optimal age of vaccination, we found that targeting older children could increase the net benefit of vaccination in settings with moderate transmission intensity (SP9 = 50%). Overall, vaccination was predicted to be potentially cost-effective in most endemic settings if priced competitively. The results are based on the assumption that the vaccine acts similarly to natural infection. This assumption is consistent with the available trial results but cannot be directly validated in the absence of additional data. Furthermore, uncertainties remain regarding the level of protection provided against disease versus infection and the rate at which vaccine-induced protection declines. Conclusions: Dengvaxia has the potential to reduce the burden of dengue disease in areas of moderate to high dengue endemicity. However, the potential risks of vaccination in areas with limited exposure to dengue as well as the local costs and benefits of routine vaccination are important considerations for the inclusion of Dengvaxia into existing immunisation programmes. These results were important inputs into WHO global policy for use of this licensed dengue vaccinSF and MJ received funding from WHO and Gavi, the Vaccine Alliance, to conduct this work. LC is a paid employee at Sanofi Pasteur. GM and JK were funded by the University of Western Australia, with computing resources provided by the Pawsey Supercomputing Centre, which is funded by the Australian Government and the Government of Western Australia. MR is funded by a Royal Society University Research Fellowship. NF, ID and DJL received research funding from the UK Medical Research Council, the UK NIHR under the Health Protection Research Unit initiative, NIGMS under the MIDAS initiative, and the Bill and Melinda Gates Foundation. IRB and DATC were funded by MIDAS Center Grant NIH/NIGMS U54-GM088491 and the Bill and Melinda Gates Foundation. DATC was also supported by NIH/NIAID R01-AI114703. TJH, IL, and CABP were funded by a Dengue Vaccine Initiative Grant to IL, NIH/NIAID R37 AI32042. THJ, IL, and KK were funded by MIDAS Center Grant NIH/NIGMS 1135 U54 GM111274. All other authors have received no specific funding to conduct this work. The funders had no role in the study design, data analyses, decision to publish or preparation of the manuscript

Organism-sediment interactions govern post-hypoxia recovery of ecosystem functioning

Hypoxia represents one of the major causes of biodiversity and ecosystem functioning loss for coastal waters. Since eutrophication-induced hypoxic events are becoming increasingly frequent and intense, understanding the response of ecosystems to hypoxia is of primary importance to understand and predict the stability of ecosystem functioning. Such ecological stability may greatly depend on the recovery patterns of communities and the return time of the system properties associated to these patterns. Here, we have examined how the reassembly of a benthic community contributed to the recovery of ecosystem functioning following experimentally-induced hypoxia in a tidal flat. We demonstrate that organism-sediment interactions that depend on organism size and relate to mobility traits and sediment reworking capacities are generally more important than recovering species richness to set the return time of the measured sediment processes and properties. Specifically, increasing macrofauna bioturbation potential during community reassembly significantly contributed to the recovery of sediment processes and properties such as denitrification, bedload sediment transport, primary production and deep pore water ammonium concentration. Such bioturbation potential was due to the replacement of the small-sized organisms that recolonised at early stages by large-sized bioturbating organisms, which had a disproportionately stronger influence on sediment. This study suggests that the complete recovery of organism-sediment interactions is a necessary condition for ecosystem functioning recovery, and that such process requires long periods after disturbance due to the slow growth of juveniles into adult stages involved in these interactions. Consequently, repeated episodes of disturbance at intervals smaller than the time needed for the system to fully recover organism-sediment interactions may greatly impair the resilience of ecosystem functioning.

Transmission dynamics of SARS-CoV-2 in a strictly-Orthodox Jewish community in the UK

Some social settings such as households and workplaces, have been identified as high risk for SARS-CoV-2 transmission. Identifying and quantifying the importance of these settings is critical for designing interventions. A tightly-knit religious community in the UK experienced a very large COVID-19 epidemic in 2020, reaching 64.3% seroprevalence within 10 months, and we surveyed this community both for serological status and individual-level attendance at particular settings. Using these data, and a network model of people and places represented as a stochastic graph rewriting system, we estimated the relative contribution of transmission in households, schools and religious institutions to the epidemic, and the relative risk of infection in each of these settings. All congregate settings were important for transmission, with some such as primary schools and places of worship having a higher share of transmission than others. We found that the model needed a higher general-community transmission rate for women (3.3-fold), and lower susceptibility to infection in children to recreate the observed serological data. The precise share of transmission in each place was related to assumptions about the internal structure of those places. Identification of key settings of transmission can allow public health interventions to be targeted at these locations

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

Tenascin-C induces inflammatory mediators and matrix degradation in osteoarthritic cartilage

<p>Abstract</p> <p>Background</p> <p>Tenascin-C (TN-C) is an extracellular matrix glycoprotein that is involved in tissue injury and repair processes. We analyzed TN-C expression in normal and osteoarthritic (OA) human cartilage, and evaluated its capacity to induce inflammatory and catabolic mediators in chondrocytes <it>in vitro</it>. The effect of TN-C on proteoglycan loss from articular cartilage in culture was also assessed.</p> <p>Methods</p> <p>TN-C in culture media, cartilage extracts, and synovial fluid of human and animal joints was quantified using a sandwich ELISA and/or analyzed by Western immunoblotting. mRNA expression of TN-C and aggrecanases were analyzed by Taqman assays. Human and bovine primary chondrocytes and/or explant culture systems were utilized to study TN-C induced inflammatory or catabolic mediators and proteoglycan loss. Total proteoglycan and aggrecanase -generated ARG-aggrecan fragments were quantified in human and rat synovial fluids by ELISA.</p> <p>Results</p> <p>TN-C protein and mRNA expression were significantly upregulated in OA cartilage with a concomitant elevation of TN-C levels in the synovial fluid of OA patients. IL-1 enhanced TN-C expression in articular cartilage. Addition of TN-C induced IL-6, PGE₂, and nitrate release and upregulated ADAMTS4 mRNA in cultured primary human and bovine chondrocytes. TN-C treatment resulted in an increased loss of proteoglycan from cartilage explants in culture. A correlation was observed between TN-C and aggrecanase generated ARG-aggrecan fragment levels in the synovial fluid of human OA joints and in the lavage of rat joints that underwent surgical induction of OA.</p> <p>Conclusions</p> <p>TN-C expression in the knee cartilage and TN-C levels measured in the synovial fluid are significantly enhanced in OA patients. Our findings suggest that the elevated levels of TN-C could induce inflammatory mediators and promote matrix degradation in OA joints.</p

Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

Background: The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. Methods: We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as “at increased risk of severe COVID-19” in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection–hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection–hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. Findings: We estimated that 1·7 billion (UI 1·0–2·4) people, comprising 22% (UI 15–28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from &lt;5% of those younger than 20 years to &gt;66% of those aged 70 years or older). We estimated that 349 million (186–787) people (4% [3–9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from &lt;1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3–12) of males to be at high risk compared with 3% (2–7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. Interpretation: About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. Funding: UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research

COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid- sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.Integrative Biolog