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101. A probabilistic model to evaluate population dietary recommendations

Author

Chalabi, Zaid, Ferguson, Elaine, Stanley, Robert, and Briend, André

Abstract

Food-based dietary recommendations (FBR) play an essential role in promoting a healthy diet. To support the process of formulating a set of population-specific FBR, a probabilistic model was developed specifically to predict the changes in the percentage of a population at risk of inadequate nutrient intakes after the adoption of alternative sets of FBR. The model simulates the distribution of the number of servings per week from food groups or food items at baseline and after the hypothetical successful adoption of alternative sets of FBR, while ensuring that the population's energy intake distribution remains similar. The simulated changes from baseline in median nutrient intakes and the percentage of the population at risk of inadequate nutrient intakes are calculated and compared across the alternative sets of FBR. The model was illustrated using a hypothetical population of 12- to 18-month-old breast-feeding children consuming a cereal-based diet low in animal source foods.

Published
2014

109. Cost-effectiveness analysis of pandemic influenza preparedness: what's missing?

Author

Drake, Tom L., Chalabi, Zaid, and Coker, Richard

Subjects
Cost benefit analysis -- Health aspects, Influenza -- Health aspects, Public health -- Health aspects, Cost benefit analysis, Health, United Nations
Abstract

Introduction Highly pathogenic pandemic influenza viruses pose a real if poorly defined risk to public health and economies. In a study of potential mortality, Murray et al. estimated that 62 [...]

Published
2012
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111. Modelling the influences of climate change and socioeconomic development on future storm surge mortality

Author

Lloyd Simon, Brown Sally, Chalabi Zaid, Nicholls Robert, and Kovats Sari

Subjects
fungi, Vulnerability, Storm surge, Climate change, Socioeconomic development, Geography, parasitic diseases, General Earth and Planetary Sciences, sense organs, skin and connective tissue diseases, Coastal flood, Health impact assessment, Environmental planning, geographic locations, General Environmental Science
Abstract

Background:Over recent decades, vulnerability to coastal flooding has decreased but remains disproportionately high in low-income countries. In the future, climate change is expected to increase di...

Published
2013

121. Emerging Themes in Epidemiology

Author

Schmidt, Wolf Peter, Genser, Bernd, Barreto, Mauricio Lima, Clasen, Thomas, Luby, Stephen P., Cairncross, Sandy, and Chalabi, Zaid

Abstract

p.358-368 Submitted by Suelen Reis (suziy.ellen@gmail.com) on 2013-08-22T12:22:43Z No. of bitstreams: 1 1742-7622-7-5.pdf: 558984 bytes, checksum: 2d7f1f99131e0c0190af43620c3871f1 (MD5) Made available in DSpace on 2013-08-22T12:22:43Z (GMT). No. of bitstreams: 1 1742-7622-7-5.pdf: 558984 bytes, checksum: 2d7f1f99131e0c0190af43620c3871f1 (MD5) Previous issue date: 2010 Background: Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP), the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling. Methods: We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error. Results: The model identified three major factors that influence sampling strategies: (1) the clustering of episodes in individuals; (2) the duration of episodes; (3) the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year) often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates. Conclusion: Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid and cost-effective.

Published
2010
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122. Epidemiology and Infection

Author

Schmidt, Wolf Peter, Genser, B., and Chalabi, Zaid

Subjects
Mathematical model, Surveillance, Statistical methods, Respiratory infection, Diarrhoea
Abstract

Texto completo: acesso restrito. p.644–653 Submitted by Suelen Reis (suziy.ellen@gmail.com) on 2013-10-01T12:35:17Z No. of bitstreams: 1 S095026880800143Xa.pdf: 262144 bytes, checksum: 8c52648d3928c5290d0e371940a2c0ee (MD5) Made available in DSpace on 2013-10-01T12:35:17Z (GMT). No. of bitstreams: 1 S095026880800143Xa.pdf: 262144 bytes, checksum: 8c52648d3928c5290d0e371940a2c0ee (MD5) Previous issue date: 2009 The measurement and analysis of common recurrent conditions such as diarrhoea, respiratory infections or fever pose methodological challenges with regard to case definition, disease surveillance and statistical analysis. In this paper we describe a flexible and robust model that can generate simulated longitudinal datasets for a range of recurrent infections, reflecting the stochastic processes that underpin the data collected in the field. It can be used to evaluate and compare alternative disease definitions, surveillance strategies and statistical methods under ‘controlled conditions’. Parameters in the model include: characterizing the distributions of the individual disease incidence and the duration of disease episodes; allowing the average disease duration to depend on an individual's number of episodes (simulating a correlation between incidence and duration); making the individual risk of disease depend on the occurrence of previous episodes (simulating autocorrelation of successive episodes); finally, incorporating seasonal variation of disease.

Published
2009
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123. An Exposure-Mortality Relationship for Residential Indoor PM2.5 Exposure from Outdoor Sources.

Author

Milner, James, Armstrong, Ben, Davies, Mike, Ridley, Ian, Chalabi, Zaid, Shrubsole, Clive, Vardoulakis, Sotiris, and Wilkinson, Paul

Subjects
PARTICULATE matter, AIR pollution, MORTALITY, HEALTH impact assessment, EPIDEMIOLOGY
Abstract

A large proportion of particulate air pollution exposure in urban areas occurs due to the penetration of outdoor pollution into the residential indoor environment. Theoretical considerations suggest that quantifying health effects due to changes to indoor particulate concentrations derived from outdoor sources requires the adjustment of exposure-response coefficients based on epidemiological studies of outdoor air. Using the PM2.5-mortality coefficient from the American Cancer Society (ACS) cohort study as an example, we developed a theoretical model to quantify the relationship between the published coefficient and one based on personal exposure, and explored how this adjusted coefficient might be applied to changes in indoor PM2.5 from outdoor sources. Using a probabilistic approach, our estimated average mortality coefficient for personal PM2.5 exposure is 30-50% greater than the ACS coefficient. However, since the indoor PM2.5 of outdoor origin accounts for only a proportion of the overall exposure, the average net adjustment required for indoor exposure is very modest. The results suggest that it is generally appropriate to apply unadjusted exposure-response functions derived from cohort studies to assess the health impact of changes in indoor particle concentrations from outdoor sources. However, it may be important to re-scale the coefficients for assessing exposures of population groups who spend a greater proportion of their time at home. [ABSTRACT FROM AUTHOR]

Published
2017
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124. Overheating in English dwellings: comparing modelled and monitored large-scale datasets.

Author

Symonds, Phil, Taylor, Jonathon, Mavrogianni, Anna, Davies, Mike, Shrubsole, Clive, Hamilton, Ian, and Chalabi, Zaid

Subjects
ENVIRONMENTAL monitoring, ENERGY consumption of buildings, HOUSING surveys, HOUSING, SIMULATION methods & models
Abstract

Monitoring and modelling studies of the indoor environment indicate that there are often discrepancies between simulation results and measurements. The availability of large monitoring datasets of domestic buildings allows for more rigorous validation of the performance of building simulation models derived from limited building information, backed by statistical significance tests and goodness-of-fit metrics. These datasets also offer the opportunity to test modelling assumptions. This paper investigates the performance of domestic housing models using EnergyPlus software to predict maximum daily indoor temperatures over the summer of 2011. Monitored maximum daily indoor temperatures from the English Housing Survey’s (EHS) Energy Follow-Up Survey (EFUS) for 823 nationally representative dwellings are compared against predictions made by EnergyPlus simulations. Due to lack of information on the characteristics of individual dwellings, the models struggle to predict maximum temperatures in individual dwellings and performance was worse on days when the outdoor maximum temperatures were high. This research indicates that unknown factors such as building characteristics, occupant behaviour and local environment makes the validation of models for individual dwellings a challenging task. The models did, however, provide an improved estimate of temperature exposure when aggregated over dwellings within a particular region. [ABSTRACT FROM PUBLISHER]

Published
2017
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135. Public health benefits of strategies to reduce greenhouse-gas emissions: food and agriculture

Author

Dangour, Alan D, Garnett, Tara, Lock, Karen, Chalabi, Zaid, Roberts, Ian, Butler, Ainslie, Butler, Colin D, Waage, Jeff, McMichael, Anthony J, Haines, Andy, Friel, Sharon, Dangour, Alan D, Garnett, Tara, Lock, Karen, Chalabi, Zaid, Roberts, Ian, Butler, Ainslie, Butler, Colin D, Waage, Jeff, McMichael, Anthony J, Haines, Andy, and Friel, Sharon

Abstract

Agricultural food production and agriculturally-related change in land use substantially contribute to greenhouse-gas emissions worldwide. Four-fifths of agricultural emissions arise from the livestock sector. Although livestock products are a source of some essential nutrients, they provide large amounts of saturated fat, which is a known risk factor for cardiovascular disease. We considered potential strategies for the agricultural sector to meet the target recommended by the UK Committee on Climate Change to reduce UK emissions from the concentrations recorded in 1990 by 80% by 2050, which would require a 50% reduction by 2030. With use of the UK as a case study, we identified that a combination of agricultural technological improvements and a 30% reduction in livestock production would be needed to meet this target; in the absence of good emissions data from Brazil, we assumed for illustrative purposes that the required reductions would be the same for our second case study in São Paulo city. We then used these data to model the potential benefits of reduced consumption of livestock products on the burden of ischaemic heart disease: disease burden would decrease by about 15% in the UK (equivalent to 2850 disability-adjusted life-years [DALYs] per million population in 1 year) and 16% in São Paulo city (equivalent to 2180 DALYs per million population in 1 year). Although likely to yield benefits to health, such a strategy will probably encounter cultural, political, and commercial resistance, and face technical challenges. Coordinated intersectoral action is needed across agricultural, nutritional, public health, and climate change communities worldwide to provide affordable, healthy, low-emission diets for all societies.

Published
2009

142. Risk analysis of housing energy efficiency interventions under model uncertainty.

Author

Chalabi, Zaid, Das, Payel, Milner, James, Davies, Mike, Hamilton, Ian, Jones, Benjamin, Shrubsole, Clive, and Wilkinson, Paul

Subjects
*HOUSING, *ENERGY consumption of buildings, *HEALTH risk assessment, *HEALTH impact assessment, *MATHEMATICAL models, *MONTE Carlo method
Abstract

Mathematical models can be used to evaluate the health impacts of housing energy efficiency interventions. However by their nature, models are subject to uncertainty and variability, which are important to quantify if used to support policy decisions. Models that are used to assess the impacts on health of housing energy efficiency interventions are likely to be based on a pair of linked component models: a building physics model which calculates changes in exposures and whose outputs then feed into a health impact model. Current methods to propagate uncertainty in a series of models, where the outputs of one model are inputs to another, invariably use Monte Carlo (MC) numerical simulation. In this paper, two methods are used to quantify the uncertainty in the impact of draught proofing on childhood asthma: the MC simulation method and a semi-analytical method based on integral transforms. Both methods give close results but it is argued that the semi-analytical method has some advantages over the MC method, particularly in quantifying the uncertainties in the main outputs of the building physics model before propagating them to the health model. [ABSTRACT FROM AUTHOR]

Published
2015
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143. Mapping the effects of urban heat island, housing, and age on excess heat-related mortality in London.

Author

Taylor, Jonathon, Wilkinson, Paul, Davies, Mike, Armstrong, Ben, Chalabi, Zaid, Mavrogianni, Anna, Symonds, Phil, Oikonomou, Eleni, and Bohnenstengel, Sylvia I.

Abstract

With the predicted increase in heatwave frequency in the UK due to climate change, there has been an increasing research focus on mortality during hot weather. This paper examines the risk of mortality in London during hot weather by combining data on population age and distribution, Urban Heat Island (UHI), and dwelling propensity to overheat due to geometry and fabric characteristics derived using building physics in order to calculate the spatial variation in heat-related mortality risk across London. Spatial variation of heat-related mortality was found to reflect background mortality rates due to population age, while dwelling characteristics were found to cause a larger variation in temperature exposure (and therefore risk) than UHI. The highest levels of excess mortality were found in areas with larger elderly populations, towards the outskirts of the Greater London Authority (GLA). [ABSTRACT FROM AUTHOR]

Published
2015
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144. A whole-economy model of the health co-benefits of strategies to reduce greenhouse gas emissions in the UK

Author

Keogh-Brown, Marcus, primary, Jensen, Henning Tarp, additional, Smith, Richard D, additional, Chalabi, Zaid, additional, Davies, Mike, additional, Dangour, Alan, additional, Edwards, Phil, additional, Garnett, Tara, additional, Givoni, Moshe, additional, Griffiths, Ulla, additional, Hamilton, Ian, additional, Jarrett, James, additional, Roberts, Ian, additional, Wilkinson, Paul, additional, Woodcock, James, additional, and Haines, Andy, additional

Published
2012
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145. O-165

Author

Milner, James, primary, Shrubsole, Clive, additional, Chalabi, Zaid, additional, Das, Payel, additional, Davies, Michael, additional, Jones, Ben, additional, Ridley, Ian, additional, and Wilkinson, Paul, additional

Published
2012
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147. List of contributors

Author

Chalabi, Zaid, George, Frank, Guerriero, Carla, Lauriola, Paolo, Leonardi, Giovanni, Luchini, Stéphane, Martuzzi, Marco, Pacelli, Antonia, Papirio, Stefano, Pirozzi, Francesco, Ranzi, Andrea, Rebolledo, L.E. Loria, Regier, Dean, Schulz, Rainer, Watson, Verity, Wright, John S.F., and Zeka, Ariana

Published
2020
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