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Article ; Online: The Gompertz Law emerges naturally from the inter-dependencies between sub-components in complex organisms.

Nielsen, Pernille Yde / Jensen, Majken K / Mitarai, Namiko / Bhatt, Samir

2024 Volume 14, Issue 1, Page(s) 1196

Abstract: Understanding and facilitating healthy aging has become a major goal in medical research and it is becoming increasingly acknowledged that there is a need for understanding the aging phenotype as a whole rather than focusing on individual factors. Here, ... ...

Abstract	Understanding and facilitating healthy aging has become a major goal in medical research and it is becoming increasingly acknowledged that there is a need for understanding the aging phenotype as a whole rather than focusing on individual factors. Here, we provide a universal explanation for the emergence of Gompertzian mortality patterns using a systems approach to describe aging in complex organisms that consist of many inter-dependent subsystems. Our model relates to the Sufficient-Component Cause Model, widely used within the field of epidemiology, and we show that including inter-dependencies between subsystems and modeling the temporal evolution of subsystem failure results in Gompertizan mortality on the population level. Our model also provides temporal trajectories of mortality-risk for the individual. These results may give insight into understanding how biological age evolves stochastically within the individual, and how this in turn leads to a natural heterogeneity of biological age in a population.
MeSH term(s)	Humans ; Models, Biological ; Aging ; Phenotype ; Biomedical Research ; Healthy Aging ; Mortality
Language	English
Publishing date	2024-01-12
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-024-51669-5
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Article ; Online: Estimating the epidemic reproduction number from temporally aggregated incidence data: A statistical modelling approach and software tool.

Nash, Rebecca K / Bhatt, Samir / Cori, Anne / Nouvellet, Pierre

PLoS computational biology

2023 Volume 19, Issue 8, Page(s) e1011439

Abstract: The time-varying reproduction number (Rt) is an important measure of epidemic transmissibility that directly informs policy decisions and the optimisation of control measures. EpiEstim is a widely used opensource software tool that uses case incidence ... ...

Abstract	The time-varying reproduction number (Rt) is an important measure of epidemic transmissibility that directly informs policy decisions and the optimisation of control measures. EpiEstim is a widely used opensource software tool that uses case incidence and the serial interval (SI, time between symptoms in a case and their infector) to estimate Rt in real-time. The incidence and the SI distribution must be provided at the same temporal resolution, which can limit the applicability of EpiEstim and other similar methods, e.g. for contexts where the time window of incidence reporting is longer than the mean SI. In the EpiEstim R package, we implement an expectation-maximisation algorithm to reconstruct daily incidence from temporally aggregated data, from which Rt can then be estimated. We assess the validity of our method using an extensive simulation study and apply it to COVID-19 and influenza data. For all datasets, the influence of intra-weekly variability in reported data was mitigated by using aggregated weekly data. Rt estimated on weekly sliding windows using incidence reconstructed from weekly data was strongly correlated with estimates from the original daily data. The simulation study revealed that Rt was well estimated in all scenarios and regardless of the temporal aggregation of the data. In the presence of weekend effects, Rt estimates from reconstructed data were more successful at recovering the true value of Rt than those obtained from reported daily data. These results show that this novel method allows Rt to be successfully recovered from aggregated data using a simple approach with very few data requirements. Additionally, by removing administrative noise when daily incidence data are reconstructed, the accuracy of Rt estimates can be improved.
MeSH term(s)	Humans ; Incidence ; COVID-19 ; Software ; Computer Simulation ; Reproduction
Language	English
Publishing date	2023-08-28
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1011439
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Book ; Online: Continuous football player tracking from discrete broadcast data

Penn, Matthew J. / Donnelly, Christl A. / Bhatt, Samir

2023

Abstract: Player tracking data remains out of reach for many professional football teams as their video feeds are not sufficiently high quality for computer vision technologies to be used. To help bridge this gap, we present a method that can estimate continuous ... ...

Abstract	Player tracking data remains out of reach for many professional football teams as their video feeds are not sufficiently high quality for computer vision technologies to be used. To help bridge this gap, we present a method that can estimate continuous full-pitch tracking data from discrete data made from broadcast footage. Such data could be collected by clubs or players at a similar cost to event data, which is widely available down to semi-professional level. We test our method using open-source tracking data, and include a version that can be applied to a large set of over 200 games with such discrete data. Comment: 12 pages, 3 figures
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Multiagent Systems
Publishing date	2023-11-24
Publishing country	us
Document type	Book ; Online
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Article ; Online: Novel Epidemic Metrics to Communicate Outbreak Risk at the Municipality Level: Dengue and Zika in the Dominican Republic.

Kingston, Rhys / Routledge, Isobel / Bhatt, Samir / Bowman, Leigh R

Viruses

2022 Volume 14, Issue 1

Abstract: Arboviruses remain a significant cause of morbidity, mortality and economic cost across the global human population. Epidemics of arboviral disease, such as Zika and dengue, also cause significant disruption to health services at local and national ... ...

Abstract	Arboviruses remain a significant cause of morbidity, mortality and economic cost across the global human population. Epidemics of arboviral disease, such as Zika and dengue, also cause significant disruption to health services at local and national levels. This study examined 2014-2016 Zika and dengue epidemic data at the sub-national level to characterise transmission across the Dominican Republic. For each municipality, spatio-temporal mapping was used to characterise disease burden, while data were age and sex standardised to quantify burden distributions among the population. In separate analyses, time-ordered data were combined with the underlying disease migration interval distribution to produce a network of likely transmission chain events, displayed using transmission chain likelihood matrices. Finally, municipal-specific reproduction numbers (R
MeSH term(s)	Cities/statistics & numerical data ; Datasets as Topic ; Dengue/epidemiology ; Dengue/prevention & control ; Dengue Virus/pathogenicity ; Dominican Republic/epidemiology ; Epidemics/prevention & control ; Epidemics/statistics & numerical data ; Humans ; Models, Statistical ; Public Health/methods ; Zika Virus/pathogenicity ; Zika Virus Infection/epidemiology ; Zika Virus Infection/prevention & control
Language	English
Publishing date	2022-01-17
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v14010162
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Article ; Online: Inference of malaria reproduction numbers in three elimination settings by combining temporal data and distance metrics.

Routledge, Isobel / Unwin, H Juliette T / Bhatt, Samir

Scientific reports

2021 Volume 11, Issue 1, Page(s) 14495

Abstract: Individual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer ... ...

Abstract	Individual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer transmission dynamics, in conjunction with additional information such as symptom onset time and genetic distance. However, in the absence of data about the flow of parasites between populations, the spatial scale of malaria transmission is often not clear. As a result, it is important to understand the impact of varying assumptions about the spatial scale of transmission on key metrics of malaria transmission, such as reproduction numbers. We developed a method which allows the flexible integration of distance metrics (such as Euclidian distance, genetic distance or accessibility matrices) with temporal information into a single inference framework to infer malaria reproduction numbers. Twelve scenarios were defined, representing different assumptions about the likelihood of transmission occurring over different geographic distances and likelihood of missing infections (as well as high and low amounts of uncertainty in this estimate). These scenarios were applied to four individual level datasets from malaria eliminating contexts to estimate individual reproduction numbers and how they varied over space and time. Model comparison suggested that including spatial information improved models as measured by second order AIC (ΔAICc), compared to time only results. Across scenarios and across datasets, including spatial information tended to increase the seasonality of temporal patterns in reproduction numbers and reduced noise in the temporal distribution of reproduction numbers. The best performing parameterisations assumed long-range transmission (> 200 km) was possible. Our approach is flexible and provides the potential to incorporate other sources of information which can be converted into distance or adjacency matrices such as travel times or molecular markers.
MeSH term(s)	Basic Reproduction Number ; China/epidemiology ; El Salvador/epidemiology ; Eswatini/epidemiology ; Humans ; Malaria/epidemiology ; Malaria/transmission ; Malaria, Falciparum/epidemiology ; Malaria, Falciparum/transmission ; Malaria, Vivax/epidemiology ; Malaria, Vivax/transmission ; Travel
Language	English
Publishing date	2021-07-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-93238-0
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Article ; Online: Implications of a highly transmissible variant of SARS-CoV-2 for children.

Ratmann, Oliver / Bhatt, Samir / Flaxman, Seth

Archives of disease in childhood

2021 Volume 106, Issue 9, Page(s) e37

MeSH term(s)	COVID-19 ; Child ; Humans ; SARS-CoV-2
Language	English
Publishing date	2021-03-30
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	524-1
ISSN	1468-2044 ; 0003-9888 ; 1359-2998
ISSN (online)	1468-2044
ISSN	0003-9888 ; 1359-2998
DOI	10.1136/archdischild-2021-321903
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Article ; Online: Sex differences in health care expenditures and mortality after spousal bereavement: A register-based Danish cohort study.

Katsiferis, Alexandros / Bhatt, Samir / Mortensen, Laust Hvas / Mishra, Swapnil / Westendorp, Rudi G J

PloS one

2023 Volume 18, Issue 3, Page(s) e0282892

Abstract: Background: Spousal bereavement is a life event that affects older people differently. We investigated the impact of spousal bereavement on medical expenditures and mortality in the general population, emphasizing on age and sex.: Methods: Data are ... ...

Abstract	Background: Spousal bereavement is a life event that affects older people differently. We investigated the impact of spousal bereavement on medical expenditures and mortality in the general population, emphasizing on age and sex. Methods: Data are from a population-based, retrospective cohort study following 924,958 Danish citizens over the age of 65 years, within 2011-2016. Changes in health care expenditures in those who suffer bereavement were compared with time matched changes among those who did not. Mortality hazards were analysed with time to event analysis. Results: A total of 77,722 (~8.4%) individuals experienced bereavement, 65.8% being females. Among males, bereavement was associated with increase of expenditures the year after, that was 42 Euros per week (95% CI, 36 to 48) larger than the non-bereaved group. The corresponding increase for females was 35 Euros per week (95% CI, 30 to 40). The increase of mortality hazards was highest in the first year after bereavement, higher in males than females, in young old and almost absent in the oldest old. Compared with the reference, mortality the year after spousal loss was 70% higher (HR 1.70 [95% CI 1.40 to 2.08]) for males aged 65-69 years and remained elevated for a period of six years. Mortality for females aged 65-69 years was 27% higher in the first year (HR 1.27, [1.07 to 1.52]), normalizing thereafter. Conclusion: Bereavement affects older people differently with younger males being most frail with limited recovery potential.
MeSH term(s)	Aged, 80 and over ; Humans ; Male ; Female ; Aged ; Cohort Studies ; Retrospective Studies ; Sex Characteristics ; Health Expenditures ; Bereavement ; Denmark/epidemiology
Language	English
Publishing date	2023-03-22
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0282892
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Article ; Online: Machine learning models of healthcare expenditures predicting mortality: A cohort study of spousal bereaved Danish individuals.

Katsiferis, Alexandros / Bhatt, Samir / Mortensen, Laust Hvas / Mishra, Swapnil / Jensen, Majken Karoline / Westendorp, Rudi G J

PloS one

2023 Volume 18, Issue 8, Page(s) e0289632

Abstract: Background: The ability to accurately predict survival in older adults is crucial as it guides clinical decision making. The added value of using health care usage for predicting mortality remains unexplored. The aim of this study was to investigate if ... ...

Abstract	Background: The ability to accurately predict survival in older adults is crucial as it guides clinical decision making. The added value of using health care usage for predicting mortality remains unexplored. The aim of this study was to investigate if temporal patterns of healthcare expenditures, can improve the predictive performance for mortality, in spousal bereaved older adults, next to other widely used sociodemographic variables. Methods: This is a population-based cohort study of 48,944 Danish citizens 65 years of age and older suffering bereavement within 2013-2016. Individuals were followed from date of spousal loss until death from all causes or 31st of December 2016, whichever came first. Healthcare expenditures were available on weekly basis for each person during the follow-up and used as predictors for mortality risk in Extreme Gradient Boosting models. The extent to which medical spending trajectories improved mortality predictions compared to models with sociodemographics, was assessed with respect to discrimination (AUC), overall prediction error (Brier score), calibration, and clinical benefit (decision curve analysis). Results: The AUC of age and sex for mortality the year after spousal loss was 70.8% [95% CI 68.8, 72.8]. The addition of sociodemographic variables led to an increase of AUC ranging from 0.9% to 3.1% but did not significantly reduce the overall prediction error. The AUC of the model combining the variables above plus medical spending usage was 80.8% [79.3, 82.4] also exhibiting smaller Brier score and better calibration. Overall, patterns of healthcare expenditures improved mortality predictions the most, also exhibiting the highest clinical benefit among the rest of the models. Conclusion: Temporal patterns of medical spending have the potential to significantly improve our assessment on who is at high risk of dying after suffering spousal loss. The proposed methodology can assist in a more efficient risk profiling and prognosis of bereaved individuals.
MeSH term(s)	Humans ; Aged ; Cohort Studies ; Health Expenditures ; Prognosis ; Machine Learning ; Denmark/epidemiology
Language	English
Publishing date	2023-08-07
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0289632
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Article ; Online: Impact of proactive and reactive vaccination strategies for health-care workers against MERS-CoV: a mathematical modelling study.

Laydon, Daniel J / Cauchemez, Simon / Hinsley, Wes R / Bhatt, Samir / Ferguson, Neil M

The Lancet. Global health

2023 Volume 11, Issue 5, Page(s) e759–e769

Abstract: Background: Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers.: ... ...

Abstract	Background: Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers. Methods: Using data from the 2013-14 Saudi Arabia epidemic, we use a counterfactual analysis on inferred transmission trees (who-infected-whom analysis) to assess the potential impact of vaccination campaigns targeting health-care workers, as quantified by the proportion of cases or deaths averted. We investigate the conditions under which proactive campaigns (ie vaccinating in anticipation of the next outbreak) would outperform reactive campaigns (ie vaccinating in response to an unfolding outbreak), considering vaccine efficacy, duration of vaccine protection, effectiveness of animal reservoir control measures, wait (time between vaccination and next outbreak, for proactive campaigns), reaction time (for reactive campaigns), and spatial level (hospital, regional, or national, for reactive campaigns). We also examine the relative efficiency (cases averted per thousand doses) of different strategies. Findings: The spatial scale of reactive campaigns is crucial. Proactive campaigns outperform campaigns that vaccinate health-care workers in response to outbreaks at their hospital, unless vaccine efficacy has waned significantly. However, reactive campaigns at the regional or national levels consistently outperform proactive campaigns, regardless of vaccine efficacy. When considering the number of cases averted per vaccine dose administered, the rank order is reversed: hospital-level reactive campaigns are most efficient, followed by regional-level reactive campaigns, with national-level and proactive campaigns being least efficient. If the number of cases required to trigger reactive vaccination increases, the performance of hospital-level campaigns is greatly reduced; the impact of regional-level campaigns is variable, but that of national-level campaigns is preserved unless triggers have high thresholds. Interpretation: Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating only health-care workers, underlining the need for countries at risk of outbreaks to stockpile vaccines when available. Funding: UK Medical Research Council, UK National Institute for Health Research, UK Research and Innovation, UK Academy of Medical Sciences, The Novo Nordisk Foundation, The Schmidt Foundation, and Investissement d'Avenir France.
MeSH term(s)	Humans ; Middle East Respiratory Syndrome Coronavirus ; Vaccination ; Health Personnel ; Disease Outbreaks/prevention & control ; Epidemics/prevention & control
Language	English
Publishing date	2023-04-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2723488-5
ISSN	2214-109X ; 2214-109X
ISSN (online)	2214-109X
ISSN	2214-109X
DOI	10.1016/S2214-109X(23)00117-1
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Article ; Online: Application of referenced thermodynamic integration to Bayesian model selection.

Hawryluk, Iwona / Mishra, Swapnil / Flaxman, Seth / Bhatt, Samir / Mellan, Thomas A

PloS one

2023 Volume 18, Issue 8, Page(s) e0289889

Abstract: Evaluating normalising constants is important across a range of topics in statistical learning, notably Bayesian model selection. However, in many realistic problems this involves the integration of analytically intractable, high-dimensional ... ...

Abstract	Evaluating normalising constants is important across a range of topics in statistical learning, notably Bayesian model selection. However, in many realistic problems this involves the integration of analytically intractable, high-dimensional distributions, and therefore requires the use of stochastic methods such as thermodynamic integration (TI). In this paper we apply a simple but under-appreciated variation of the TI method, here referred to as referenced TI, which computes a single model's normalising constant in an efficient way by using a judiciously chosen reference density. The advantages of the approach and theoretical considerations are set out, along with pedagogical 1 and 2D examples. The approach is shown to be useful in practice when applied to a real problem -to perform model selection for a semi-mechanistic hierarchical Bayesian model of COVID-19 transmission in South Korea involving the integration of a 200D density.
MeSH term(s)	Humans ; Bayes Theorem ; COVID-19 ; Thermodynamics ; Republic of Korea
Language	English
Publishing date	2023-08-14
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0289889
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