Coronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the countries suffering the most with the COVID-19 epidemic. It is important to ...predict the epidemic trend of the COVID-19 epidemic in Italy to help develop public health strategies.
We used time-series data of COVID-19 from Jan 22 2020 to Apr 02 2020. An infectious disease dynamic extended susceptible-infected-removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with a similar total population number to Italy, was used as a comparative item.
In the eSIR model, we estimated that the mean of basic reproductive number for COVID-19 was 4.34 (95% CI, 3.04-6.00) in Italy and 3.16 (95% CI, 1.73-5.25) in Hunan. There would be a total of 182 051 infected cases (95%CI:116 114-274 378) under the current country blockade and the endpoint would be Aug 05 in Italy.
Italy's current strict measures can efficaciously prevent the further spread of COVID-19 and should be maintained. Necessary strict public health measures should be implemented as soon as possible in other European countries with a high number of COVID-19 cases. The most effective strategy needs to be confirmed in further studies.
When assessing spatially extended complex systems, one can rarely sample the states of all components. We show that this spatial subsampling typically leads to severe underestimation of the risk of ...instability in systems with propagating events. We derive a subsampling-invariant estimator, and demonstrate that it correctly infers the infectiousness of various diseases under subsampling, making it particularly useful in countries with unreliable case reports. In neuroscience, recordings are strongly limited by subsampling. Here, the subsampling-invariant estimator allows to revisit two prominent hypotheses about the brain's collective spiking dynamics: asynchronous-irregular or critical. We identify consistently for rat, cat, and monkey a state that combines features of both and allows input to reverberate in the network for hundreds of milliseconds. Overall, owing to its ready applicability, the novel estimator paves the way to novel insight for the study of spatially extended dynamical systems.
Several vaccines for SARS-CoV-2 are expected to be available in Australia in 2021. Initial supply is limited and will require a judicious vaccination strategy until supply is unrestricted. If ...vaccines have efficacy as post-exposure prophylaxis (PEP) in contacts, this provides more policy options. We used a deterministic mathematical model of epidemic response with limited supply (age-targeted or ring vaccination) and mass vaccination for the State of New South Wales (NSW) in Australia. For targeted vaccination, the effectiveness of vaccinating health workers, young people and older adults was compared. For mass vaccination, we tested varying vaccine efficacy (VE) and distribution capacities. With a limited vaccine stockpile enough for 1 million people in NSW, if there is efficacy as PEP, the most efficient way to control COVID-19 will be ring vaccination, however at least 90% of contacts per case needs to be traced and vaccinated. Health worker vaccination is required for health system resilience. Age based strategies with restricted doses make minimal impact on the epidemic, but vaccinating older people prevents more deaths. Herd immunity can only be achieved with mass vaccination. With 90% VE against all infection, herd immunity can be achieved by vaccinating 66% of the population. A vaccine with less than 70% VE cannot achieve herd immunity and will result in ongoing risk of outbreaks. For mass vaccination, distributing at least 60,000 doses per day is required to achieve control. Slower rates of vaccination will result in the population living with COVID-19 longer, and higher cases and deaths.
AbstractThe inherently variable nature of epidemics renders predictions of when and where infection is expected to occur challenging. Differences in pathogen strain composition, diversity, fitness, ...and spatial distribution are generally ignored in epidemiological modeling and are rarely studied in natural populations, yet they may be important drivers of epidemic trajectories. To examine how these factors are linked to epidemics in natural host populations, we collected epidemiological and genetic data from 15 populations of the powdery mildew fungus,
, on
in the Åland Islands, Finland. In each population, we tracked spatiotemporal disease progression throughout one epidemic season and coupled our survey of infection with intensive field sampling of the pathogen. We found that strain composition varied greatly among populations in the landscape. Within populations, strain composition was driven by the sequence of strain activity: early-active strains reached higher abundances, leading to consistent strain compositions over time. Co-occurring strains also varied in their contribution to the growth of the local epidemic, and these fitness inequalities were linked to epidemic dynamics: a higher proportion of hosts became infected in populations containing strains that were more similar in fitness. Epidemic trajectories in the populations were also linked to strain diversity and spatial dynamics: higher infection rates occurred in populations containing higher strain diversity, while spatially clustered epidemics experienced lower infection rates. Together, our results suggest that spatial and/or temporal variation in the strain composition, diversity, and fitness of pathogen populations are important factors generating variation in epidemiological trajectories among infected host populations.
We introduce conditional quenched mean-field (cQMF) method for recurrent-state susceptible–infected–susceptible epidemics in complex networks. This novel analytic method and three other competing ...models are systematically investigated and compared against continuous-time Gillespie algorithm-based computer simulations. We find that analytical results of our cQMF method are in good agreement with numerical simulations on Erdős–Rényi random graphs and various scale-free network configurations. While being formally similar to the recurrent dynamic message passing (rDMP) model, our cQMF method clearly outperforms rDMP in the prediction of the final epidemic size. Our method offers an advanced approach to modeling recurrent-state epidemic dynamics, where individuals face repeated infections in the course of their lifetime due to continuous virus evolution or waning immunity, as in seasonal influenza or pertussis.
•We introduce conditional quenched mean-field (cQMF) method for recurrent-state epidemics in complex networks.•Our method is compared against three competing mathematical models and Gillespie algorithm-based simulations.•Our analytical results are in good agreement with numerical simulations on Erdős–Rényi random graphs and scale-free networks.•Our cQMF method is better in predicting the final epidemic size than the recurrent dynamic message passing or the quenched mean-field models.•Our method offers an advanced approach to modeling recurrent-state epidemic dynamics such as those of seasonal influenza.
Pre-exposure prophylaxis Kerzner, Michael; De, Anindya K; Yee, Randy ...
PloS one,
04/2022, Volume:
17, Issue:
4
Journal Article
Peer reviewed
Mitigation measures for the first wave of the COVID-19 pandemic and burden on health systems created challenges for pre-exposure prophylaxis (PrEP) service delivery. We examined PrEP uptake in PEPFAR ...programs before and after the start of the COVID-19 pandemic. We studied two PEPFAR program monitoring indicators, using routine Monitoring, Evaluation, Reporting (MER) indicators capturing uptake of PrEP (PrEP_NEW) and overall use of PrEP (PrEP_CURR). We also analyzed descriptive program narratives to understand successes and challenges field teams encountered after the start of the COVID-19 pandemic. To assess changes in coverage of PrEP across 21 countries, we calculated the "PrEP to need ratio" (PnR) using a published methodology. We defined the pre-COVID time period as April 1, 2019 -March 31, 2020 and the COVID time period as April 1, 2020 -March 31, 2021. The total number of persons who initiated PrEP increased by 157% from 233,250 in the pre-COVID-19 period compared with 599,935 in the COVID-19 period. All countries, except five, noted significant increases in PrEP uptake. PrEP uptake among adolescent girls and young women (AGYW) increased by 159% from 80,452 AGYW in the pre-COVID-19 period to 208,607 AGYW in the COVID-19 period. There were 77,430 key populations (KP) initiated on PrEP in the pre-COVID-19 period and 209,114 KP initiated in the COVID-19 period (a 170% increase). The PnR increased 214% in the COVID-19 period across all PEPFAR-supported countries. Adaptations, such as multi-month dispensing (MMD) of PrEP; virtual demand creation activities; decentralized, community-based and virtual service delivery, were implemented to maintain PrEP services. PEPFAR programs continued to maintain and initiate new clients on PrEP despite the challenges posed by the COVID-19 pandemic. Adaptations such as MMD of PrEP and use of technology were vital in expanding service delivery and increasing PrEP coverage.
End stage kidney disease increase the risk of COVID-19 related death but how the kidney replacement strategy should be adapted during the pandemic is unknown. Chronic hemodialysis makes social ...distancing difficult to achieve. Alternatively, kidney transplantation could increase the severity of COVID-19 due to therapeutic immunosuppression and contribute to saturation of intensive care units. For these reasons, kidney transplantation was suspended in France during the first epidemic wave. Here, we retrospectively evaluated this strategy by comparing the overall and COVID-19 related mortality in kidney transplant recipients and candidates over the last three years. Cross-interrogation of two national registries for the period 1 March and 1 June 2020, identified 275 deaths among the 42812 kidney transplant recipients and 144 deaths among the 16210 candidates. This represents an excess of deaths for both populations, as compared with the same period the two previous years (mean of two previous years: 253 in recipients and 112 in candidates). This difference was integrally explained by COVID-19, which accounted for 44% (122) and 42% (60) of the deaths in recipients and candidates, respectively. Taking into account the size of the two populations and the geographical heterogeneity of virus circulation, we found that the excess of risk of death due to COVID-19 was similar for recipients and candidates in high viral risk area but four-fold higher for candidates in the low viral risk area. Thus, in case of a second epidemic wave, kidney transplantation should be suspended in high viral risk areas but maintained outside those areas, both to reduce the excess of deaths of candidates and avoid wasting precious resources.
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We define and study an open stochastic SIR (Susceptible–Infected–Removed) model on a graph in order to describe the spread of an epidemic on a cattle trade network with epidemiological and ...demographic dynamics occurring over the same time scale. Population transition intensities are assumed to be density-dependent with a constant component, the amplitude of which determines the overall scale of the population process. Standard branching approximation results for the epidemic process are first given, along with a numerical computation method for the probability of a major epidemic outbreak. This procedure is illustrated using real data on trade-related cattle movements from a densely populated livestock farming region in western France (Finistère) and epidemiological parameters corresponding to an infectious epizootic disease. Then we exhibit an exponential lower bound for the extinction time and the total size of the epidemic in the stable endemic case as a scaling parameter goes to infinity using results inspired by the Freidlin–Wentzell theory of large deviations from a dynamical system.
Drug overdoses involving opioid analgesics have increased dramatically since 1999, representing one of the United States’ top public health crises. Opioids have legitimate medical functions, but they ...are often diverted, suggesting a tradeoff between improving medical access and nonmedical abuse. We provide causal estimates of the relationship between the medical opioid supply and drug overdoses using Medicare Part D as a differential shock to the geographic distribution of opioids. Our estimates imply that a 10% increase in opioid medical supply leads to a 7.1% increase in opioid-related deaths among the Medicare-ineligible population, suggesting substantial diversion from medical markets.
A number of nations were forced to declare a total shutdown due to COVID-19 infection, as extreme measure to cope with dramatic impact of the pandemic, with remarkable consequences both in terms of ...negative health outcomes and economic loses. However, in many countries a "Phase-2" is approaching and many activities will re-open soon, although with some differences depending on the severity of the outbreak experienced and SARS-COV-2 estimated diffusion in the general population. At the present, possible relapses of the epidemic cannot be excluded until effective vaccines or immunoprophylaxis with human recombinant antibodies will be properly set up and commercialized. COVD-19-related quarantines have triggered serious social challenges, so that decision makers are concerned about the risk of wasting all the sacrifices imposed to the people in these months of quarantine. The availability of possible early predictive indicators of future epidemic relapses would be very useful for public health purposes, and could potentially prevent the suspension of entire national economic systems. On 16 March, a Position Paper launched by the Italian Society of Environmental Medicine (SIMA) hypothesized for the first time a possible link between the dramatic impact of COVID-19 outbreak in Northern Italy and the high concentrations of particulate matter (PM
and PM
) that characterize this area, along with its well-known specific climatic conditions. Thereafter, a survey carried out in the U.S. by the Harvard School of Public Health suggested a strong association between increases in particulate matter concentration and mortality rates due to COVID-19. The presence of SARS-COV-2 RNA on the particulate matter of Bergamo, which is not far from Milan and represents the epicenter of the Italian epidemic, seems to confirm (at least in case of atmospheric stability and high PM concentrations, as it usually occurs in Northern Italy) that the virus can create clusters with the particles and be carried and detected on PM
. Although no assumptions can be made concerning the link between this first experimental finding and COVID-19 outbreak progression or severity, the presence of SARS-COV-2 RNA on PM
of outdoor air samples in any city of the world could represent a potential early indicator of COVID-19 diffusion. Searching for the viral genome on particulate matter could therefore be explored among the possible strategies for adopting all the necessary preventive measures before future epidemics start.
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