Adaptive staffing can mitigate essential worker disease and absenteeism in an emerging epidemic.
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ABSTRACT:
SUBMITTER: Aguilar E
PROVIDER: S-EPMC8403949 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The emergence and global impact of the novel influenza A(H1N1)v highlights the continuous threat to public health posed by a steady stream of new and unexpected infectious disease outbreaks in animals and humans. Once an emerging epidemic is detected, public health authorities will attempt to mitigate the epidemic by, among other measures, reducing further spread as much as possible. Scarce and/or costly control measures such as vaccines, anti-infective drugs, and social distancing must be allocated while epidemiological characteristics of the disease remain uncertain. Here we present first principles for allocating scarce resources with limited data. We show that under a broad class of assumptions, the simple rule of targeting intervention measures at the group with the highest risk of infection per individual will achieve the largest reduction in the transmission potential of a novel infection. For vaccination of susceptible persons, the appropriate risk measure is force of infection; for social distancing, the appropriate risk measure is incidence of infection. Unlike existing methods that rely on detailed knowledge of group-specific transmission rates, the method described here can be implemented using only data that are readily available during an epidemic, and allows ready adaptation as the epidemic progresses. The need to observe risk of infection helps to focus the ongoing planning and design of new infectious disease surveillance programs; from the presented first principles for allocating scarce resources, we can adjust the prioritization of groups for intervention when new observations on an emerging epidemic become available.
| S-EPMC2818907 | biostudies-literature
Project description:Due to the increasing prevalence of nonalcoholic steatohepatitis (NASH) and its associated health burden, there is a high need to develop therapeutic strategies for patients with this disease. Unfortunately, its long and asymptomatic natural history, the uncertainties about disease progression, the fact that most patients are undiagnosed, and the requirement for sequential liver biopsies create substantial challenges for clinical development. Adaptive design methods are increasingly used in clinical research as they provide the flexibility and efficiency for identifying potential signals of clinical benefit of the test treatment under investigation and make prompt preplanned adaptations without undermining the validity or integrity of the trial. Given the high unmet medical need and the lack of validated surrogate endpoints in NASH, the use of adaptive design methods appears reasonable. Furthermore, due to the limited number of patients willing to have multiple liver biopsies and the need for long-term exposure to assess an impact in outcomes, a continuous seamless adaptive design may reduce the overall sample size while allowing patients to continue after each one of the phases. Here, we review strategic frameworks that include potential surrogate endpoints as well as statistical and logistical approaches that could be considered for applying adaptive designs to clinical trials in NASH with the goal of facilitating drug development for this growing medical need. (Hepatology Communications 2017;1:577-585).
| S-EPMC5721443 | biostudies-literature
Project description:ObjectivesThe COVID-19 pandemic increases healthcare worker (HCW) absenteeism. The bacillus Calmette-Guérin (BCG) vaccine may provide non-specific protection against respiratory infections through enhancement of trained immunity. We investigated the impact of BCG vaccination on HCW absenteeism during the COVID-19 pandemic.MethodsHCWs exposed to COVID-19 patients in nine Dutch hospitals were randomized to BCG vaccine or placebo in a 1:1 ratio, and followed for one year using a mobile phone application. The primary endpoint was the self-reported number of days of unplanned absenteeism for any reason. Secondary endpoints included documented COVID-19, acute respiratory symptoms or fever. This was an investigator-funded study, registered at ClinicalTrials.gov (NCT03987919).ResultsIn March/April 2020, 1511 HCWs were enrolled. The median duration of follow-up was 357 person-days (interquartile range [IQR], 351 to 361). Unplanned absenteeism for any reason was observed in 2.8% of planned working days in the BCG group and 2.7% in the placebo group (adjusted relative risk 0.94; 95% credible interval, 0.78-1.15). Cumulative incidences of documented COVID-19 were 14.2% in the BCG and 15.2% in the placebo group (adjusted hazard ratio (aHR) 0.94; 95% confidence interval (CI), 0.72-1.24). First episodes of self-reported acute respiratory symptoms or fever occurred in 490 (66.2%) and 443 (60.2%) participants, respectively (aHR: 1.13; 95% CI, 0.99-1.28). Thirty-one serious adverse events were reported (13 after BCG, 18 after placebo), none considered related to study medication.ConclusionsDuring the COVID-19 pandemic, BCG-vaccination of HCW exposed to COVID-19 patients did not reduce unplanned absenteeism nor documented COVID-19.
| S-EPMC9046133 | biostudies-literature
Project description:Non-alcoholic fatty liver disease (NAFLD) affects over 30% of the United States population and is projected to become a leading cause of chronic liver disease by 2020. As a result, the economic and societal burden of NAFLD is far-reaching. The cost of managing NAFLD complications has an estimated 10 year economic burden of $908 billion. This review provides an overview of current knowledge on NAFLD, with emphasis on identifying gaps in its diagnosis and management, and proposes future directions to address these limitations. Despite the increasing prevalence of NAFLD, there is limited knowledge and practice regarding its natural history, staging, diagnosis, and management. Though a challenging task, opportunities for bridging these gaps should focus on the development of noninvasive biomarkers, the elucidation of biological pathways, the creation of up-to-date screening guidelines, and the organization of clinical trials of longer duration to determine clinical endpoints and assess the safety of new treatment options.
| S-EPMC5924851 | biostudies-literature
Project description:Animals and plants are increasingly suffering from diseases caused by fungi and oomycetes. These emerging pathogens are now recognized as a global threat to biodiversity and food security. Among oomycetes, Saprolegnia species cause significant declines in fish and amphibian populations. Fish eggs have an immature adaptive immune system and depend on nonspecific innate defences to ward off pathogens. Here, meta-taxonomic analyses revealed that Atlantic salmon eggs are home to diverse fungal, oomycete and bacterial communities. Although virulent Saprolegnia isolates were found in all salmon egg samples, a low incidence of Saprolegniosis was strongly correlated with a high richness and abundance of specific commensal Actinobacteria, with the genus Frondihabitans (Microbacteriaceae) effectively inhibiting attachment of Saprolegniato salmon eggs. These results highlight that fundamental insights into microbial landscapes of fish eggs may provide new sustainable means to mitigate emerging diseases.
| S-EPMC4184010 | biostudies-literature
Project description:BackgroundAdaptive designs offer great promise in improving the efficiency and patient-benefit of clinical trials. An important barrier to further increased use is a lack of understanding about which additional resources are required to conduct a high-quality adaptive clinical trial, compared to a traditional fixed design. The Costing Adaptive Trials (CAT) project investigated which additional resources may be required to support adaptive trials.MethodsWe conducted a mock costing exercise amongst seven Clinical Trials Units (CTUs) in the UK. Five scenarios were developed, derived from funded clinical trials, where a non-adaptive version and an adaptive version were described. Each scenario represented a different type of adaptive design. CTU staff were asked to provide the costs and staff time they estimated would be needed to support the trial, categorised into specified areas (e.g. statistics, data management, trial management). This was calculated separately for the non-adaptive and adaptive version of the trial, allowing paired comparisons. Interviews with 10 CTU staff who had completed the costing exercise were conducted by qualitative researchers to explore reasons for similarities and differences.ResultsEstimated resources associated with conducting an adaptive trial were always (moderately) higher than for the non-adaptive equivalent. The median increase was between 2 and 4% for all scenarios, except for sample size re-estimation which was 26.5% (as the adaptive design could lead to a lengthened study period). The highest increase was for statistical staff, with lower increases for data management and trial management staff. The percentage increase in resources varied across different CTUs. The interviews identified possible explanations for differences, including (1) experience in adaptive trials, (2) the complexity of the non-adaptive and adaptive design, and (3) the extent of non-trial specific core infrastructure funding the CTU had.ConclusionsThis work sheds light on additional resources required to adequately support a high-quality adaptive trial. The percentage increase in costs for supporting an adaptive trial was generally modest and should not be a barrier to adaptive designs being cost-effective to use in practice. Informed by the results of this research, guidance for investigators and funders will be developed on appropriately resourcing adaptive trials.
| S-EPMC8545558 | biostudies-literature
Project description:IntroductionAbsenteeism of frontline health workers in public sector facilities is widespread in low-income countries. There is little quantitative evidence on how health worker absenteeism influences patient treatment seeking behavior, though low public sector utilization and heavy reliance on the informal sector are well documented in low-income settings.MethodsUsing a unique panel dataset covering health facilities and households over a 10-month period in Uganda, we investigate the extent to which health worker absenteeism (defined as zero health workers present at a health facility) impacts patient care seeking behavior, testing, and treatment.ResultsWe find high rates of health worker absenteeism at public sector health facilities, with most of the absenteeism occurring at lower level public health clinics. On average, no health worker was present in 42% of all days monitored in lowest level public health clinics, whereas this number was less than 5% in high level public hospitals and private facilities. In our preferred empirical model with household fixed effects, we find that health worker absenteeism reduces the odds that a patient seeks care in the public sector (OR = 0.65, 95% CI = 0.44-0.95) and receives malaria testing (OR = 0.73, 95% CI = 0.53-0.99) and increases the odds of paying out-of-pocket for treatment (OR = 1.41, 95% CI = 1.10-1.80). The estimated differences in care-seeking are larger for children under-five than for the overall study population.ConclusionsThe impact of health worker absenteeism on the quality of care received as well as the financial burden faced by households in sub-Saharan Africa is substantial.
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Project description:The enteric disease of swine recognized in the early 1970s in Europe was initially described as "epidemic viral diarrhea" and is now termed "porcine epidemic diarrhea (PED)". The coronavirus referred to as PED virus (PEDV) was determined to be the etiologic agent of this disease in the late 1970s. Since then the disease has been reported in Europe and Asia, but the most severe outbreaks have occurred predominantly in Asian swine-producing countries. Most recently, PED first emerged in early 2013 in the United States that caused high morbidity and mortality associated with PED, remarkably affecting US pig production, and spread further to Canada and Mexico. Soon thereafter, large-scale PED epidemics recurred through the pork industry in South Korea, Japan, and Taiwan. These recent outbreaks and global re-emergence of PED require urgent attention and deeper understanding of PEDV biology and pathogenic mechanisms. This paper highlights the current knowledge of molecular epidemiology, diagnosis, and pathogenesis of PEDV, as well as prevention and control measures against PEDV infection. More information about the virus and the disease is still necessary for the development of effective vaccines and control strategies. It is hoped that this review will stimulate further basic and applied studies and encourage collaboration among producers, researchers, and swine veterinarians to provide answers that improve our understanding of PEDV and PED in an effort to eliminate this economically significant viral disease, which emerged or re-emerged worldwide.
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Project description:We study the standard SIS model of epidemic spreading on networks where individuals have a fluctuating number of connections around a preferred degree ?. Using very simple rules for forming such preferred degree networks, we find some unusual statistical properties not found in familiar Erdös-Rényi or scale free networks. By letting ? depend on the fraction of infected individuals, we model the behavioral changes in response to how the extent of the epidemic is perceived. In our models, the behavioral adaptations can be either 'blind' or 'selective'--depending on whether a node adapts by cutting or adding links to randomly chosen partners or selectively, based on the state of the partner. For a frozen preferred network, we find that the infection threshold follows the heterogeneous mean field result ?(c)/? = <?>/<?2> and the phase diagram matches the predictions of the annealed adjacency matrix (AAM) approach. With 'blind' adaptations, although the epidemic threshold remains unchanged, the infection level is substantially affected, depending on the details of the adaptation. The 'selective' adaptive SIS models are most interesting. Both the threshold and the level of infection changes, controlled not only by how the adaptations are implemented but also how often the nodes cut/add links (compared to the time scales of the epidemic spreading). A simple mean field theory is presented for the selective adaptations which capture the qualitative and some of the quantitative features of the infection phase diagram.
| S-EPMC3506630 | biostudies-literature
Project description:During 2011 Schmallenberg virus (SBV) presented as a novel disease of cattle and sheep that had apparently spread through northern Europe over a relatively short period of time, but has yet to infect Scotland. This paper describes the development of a model of SBV spread applied to Scotland in the event of an incursion. This model shows that SBV spread is very sensitive to the temperature, with relatively little spread and few reproductive losses predicted in years with average temperatures but extensive spread (>1 million animals infected) and substantial reproductive losses in the hottest years. These results indicate that it is possible for SBV to spread in Scotland, however spread is limited by climatic conditions and the timing of introduction. Further results show that the transmission kernel shape and extrinsic incubation period parameter have a non-linear effect on disease transmission, so a greater understanding of the SBV transmission parameters is required.
| S-EPMC3560360 | biostudies-literature