Disease surveillance using a hidden Markov model

<p>Abstract</p> <p>Background</p> <p>Routine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable for use with sparse small area count data and requires little baseline data.</p> <p>Methods</p> <p>A Bayesian HMM was designed to monitor routinely collected notifiable disease data that are aggregated by residential postcode. Semi-synthetic data were used to evaluate the algorithm and compare outbreak detection performance with the established Early Aberration Reporting System (EARS) algorithms and a negative binomial cusum.</p> <p>Results</p> <p>Algorithm performance varied according to the desired false alarm rate for surveillance. At false alarm rates around 0.05, the cusum-based algorithms provided the best overall outbreak detection performance, having similar sensitivity to the HMMs and a shorter average time to detection. At false alarm rates around 0.01, the HMM algorithms provided the best overall outbreak detection performance, having higher sensitivity than the cusum-based Methods and a generally shorter time to detection for larger outbreaks. Overall, the 14-day HMM had a significantly greater area under the receiver operator characteristic curve than the EARS C3 and 7-day negative binomial cusum algorithms.</p> <p>Conclusion</p> <p>Our findings suggest that the HMM provides an effective method for the surveillance of sparse small area notifiable disease data at low false alarm rates. Further investigations are required to evaluation algorithm performance across other diseases and surveillance contexts.</p

The importance of post-translocation monitoring of habitat use and population growth: insights from a Seychelles Warbler (Acrocephalus sechellensis) translocation

Translocations are a valuable tool within conservation, and when performed successfully can rescue species from extinction. However, to label a translocation a success, extensive post-translocation monitoring is required, ensuring the population is growing at the expected rate. In 2011, a habitat assessment identified Frégate Island as a suitable island to host a Seychelles Warbler (Acrocephalus sechellensis) population. Later that year, 59 birds were translocated from Cousin Island to Frégate Island. Here, we determine Seychelles Warbler habitat use and population growth on Frégate Island, assessing the status of the translocation and identifying any interventions that may be required. We found that territory quality, an important predictor of fledgling production on Cousin Island, was a poor predictor of bird presence on Frégate Island. Instead, tree diversity, middle-storey vegetation density, and broad-leafed vegetation density all predicted bird presence positively. A habitat suitability map based on these results suggests most of Frégate Island contains either a suitable or a moderately suitable habitat, with patches of unsuitable overgrown coconut plantation. To achieve the maximum potential Seychelles Warbler population size on Frégate Island, we recommend habitat regeneration, such that the highly diverse subset of broad-leafed trees and a dense middle storey should be protected and replace the unsuitable coconut. Frégate Island’s Seychelles Warbler population has grown to 141 birds since the release, the slowest growth rate of all Seychelles Warbler translocations; the cause of this is unclear. This study highlights the value of post-translocation monitoring, identifying habitat use and areas requiring restoration, and ultimately ensuring that the population is growing

Upregulated IL-1β in dysferlin-deficient muscle attenuates regeneration by blunting the response to pro-inflammatory macrophages.

BACKGROUND: Loss-of-function mutations in the dysferlin gene (DYSF) result in a family of muscle disorders known collectively as the dysferlinopathies. Dysferlin-deficient muscle is characterized by inflammatory foci and macrophage infiltration with subsequent decline in muscle function. Whereas macrophages function to remove necrotic tissue in acute injury, their prevalence in chronic myopathy is thought to inhibit resolution of muscle regeneration. Two major classes of macrophages, classical (M1) and alternative (M2a), play distinct roles during the acute injury process. However, their individual roles in chronic myopathy remain unclear and were explored in this study. METHODS: To test the roles of the two macrophage phenotypes on regeneration in dysferlin-deficient muscle, we developed an in vitro co-culture model of macrophages and muscle cells. We assayed the co-cultures using ELISA and cytokine arrays to identify secreted factors and performed transcriptome analysis of molecular networks induced in the myoblasts. RESULTS: Dysferlin-deficient muscle contained an excess of M1 macrophage markers, compared with WT, and regenerated poorly in response to toxin injury. Co-culturing macrophages with muscle cells showed that M1 macrophages inhibit muscle regeneration whereas M2a macrophages promote it, especially in dysferlin-deficient muscle cells. Examination of soluble factors released in the co-cultures and transcriptome analysis implicated two soluble factors in mediating the effects: IL-1β and IL-4, which during acute injury are secreted from M1 and M2a macrophages, respectively. To test the roles of these two factors in dysferlin-deficient muscle, myoblasts were treated with IL-4, which improved muscle differentiation, or IL-1β, which inhibited it. Importantly, blockade of IL-1β signaling significantly improved differentiation of dysferlin-deficient cells. CONCLUSIONS: We propose that the inhibitory effects of M1 macrophages on myogenesis are mediated by IL-1β signals and suppression of the M1-mediated immune response may improve muscle regeneration in dysferlin deficiency. Our studies identify a potential therapeutic approach to promote muscle regeneration in dystrophic muscle

Transcriptome Analysis of Synaptoneurosomes Identifies Neuroplasticity Genes Overexpressed in Incipient Alzheimer's Disease

In Alzheimer's disease (AD), early deficits in learning and memory are a consequence of synaptic modification induced by toxic beta-amyloid oligomers (oAβ). To identify immediate molecular targets downstream of oAβ binding, we prepared synaptoneurosomes from prefrontal cortex of control and incipient AD (IAD) patients, and isolated mRNAs for comparison of gene expression. This novel approach concentrates synaptic mRNA, thereby increasing the ratio of synaptic to somal mRNA and allowing discrimination of expression changes in synaptically localized genes. In IAD patients, global measures of cognition declined with increasing levels of dimeric Aβ (dAβ). These patients also showed increased expression of neuroplasticity related genes, many encoding 3′UTR consensus sequences that regulate translation in the synapse. An increase in mRNA encoding the GluR2 subunit of the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) was paralleled by elevated expression of the corresponding protein in IAD. These results imply a functional impact on synaptic transmission as GluR2, if inserted, maintains the receptors in a low conductance state. Some overexpressed genes may induce early deficits in cognition and others compensatory mechanisms, providing targets for intervention to moderate the response to dAβ

Determinants of recovery from post-COVID-19 dyspnoea: analysis of UK prospective cohorts of hospitalised COVID-19 patients and community-based controls

Background The risk factors for recovery from COVID-19 dyspnoea are poorly understood. We investigated determinants of recovery from dyspnoea in adults with COVID-19 and compared these to determinants of recovery from non-COVID-19 dyspnoea. Methods We used data from two prospective cohort studies: PHOSP-COVID (patients hospitalised between March 2020 and April 2021 with COVID-19) and COVIDENCE UK (community cohort studied over the same time period). PHOSP-COVID data were collected during hospitalisation and at 5-month and 1-year follow-up visits. COVIDENCE UK data were obtained through baseline and monthly online questionnaires. Dyspnoea was measured in both cohorts with the Medical Research Council Dyspnoea Scale. We used multivariable logistic regression to identify determinants associated with a reduction in dyspnoea between 5-month and 1-year follow-up. Findings We included 990 PHOSP-COVID and 3309 COVIDENCE UK participants. We observed higher odds of improvement between 5-month and 1-year follow-up among PHOSP-COVID participants who were younger (odds ratio 1.02 per year, 95% CI 1.01–1.03), male (1.54, 1.16–2.04), neither obese nor severely obese (1.82, 1.06–3.13 and 4.19, 2.14–8.19, respectively), had no pre-existing anxiety or depression (1.56, 1.09–2.22) or cardiovascular disease (1.33, 1.00–1.79), and shorter hospital admission (1.01 per day, 1.00–1.02). Similar associations were found in those recovering from non-COVID-19 dyspnoea, excluding age (and length of hospital admission). Interpretation Factors associated with dyspnoea recovery at 1-year post-discharge among patients hospitalised with COVID-19 were similar to those among community controls without COVID-19. Funding PHOSP-COVID is supported by a grant from the MRC-UK Research and Innovation and the Department of Health and Social Care through the National Institute for Health Research (NIHR) rapid response panel to tackle COVID-19. The views expressed in the publication are those of the author(s) and not necessarily those of the National Health Service (NHS), the NIHR or the Department of Health and Social Care. COVIDENCE UK is supported by the UK Research and Innovation, the National Institute for Health Research, and Barts Charity. The views expressed are those of the authors and not necessarily those of the funders