Suchergebnisse

Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- List of Figures -- List of Tables -- 1: Introduction -- 1.1 Motivating example: mapping river-blindness in Africa -- 1.2 Empirical or mechanistic models -- 1.3 What is in this book? -- 2: Regression modelling for spatially referenced data -- 2.1 Linear regression models -- 2.1.1 Malnutrition in Ghana -- 2.2 Generalised linear models -- 2.2.1 Logistic Binomial regression: river-blindness in Liberia -- 2.2.2 Log-linear Poisson regression: abundance of Anopheles Gambiae mosquitoes in Southern Cameroon -- 2.3 Questioning the assumption of independence -- 2.3.1 Testing for residual spatial correlation: the empirical variogram -- 3: Theory -- 3.1 Gaussian processes -- 3.2 Families of spatial correlation functions -- 3.2.1 The exponential family -- 3.2.2 The Matérn family -- 3.2.3 The spherical family -- 3.2.4 The theoretical variogram and the nugget variance -- 3.3 Statistical inference -- 3.3.1 Likelihood-based inference -- 3.4 Bayesian Inference -- 3.5 Predictive inference -- 3.6 Approximations to Gaussian processes -- 3.6.1 Low-rank approximations -- 3.6.2 Gaussian Markov random field approximations via stochastic partial differential equations -- 4: The linear geostatistical model -- 4.1 Model formulation -- 4.2 Inference -- 4.2.1 Likelihood-based inference -- 4.2.1.1 Maximum likelihood estimation -- 4.2.2 Bayesian inference -- 4.2.3 Trans-Gaussian models -- 4.3 Model validation -- 4.3.1 Scenario 1: omission of the nugget effect -- 4.3.2 Scenario 2: miss-specification of the smoothness parameter -- 4.3.3 Scenario 3: non-Gaussian data -- 4.4 Spatial prediction -- 4.5 Applications -- 4.5.1 Heavy metal monitoring in Galicia -- 4.5.2 Malnutrition in Ghana (continued) -- 4.5.2.1 Spatial predictions for the target population.

Second‐order methods provide a natural starting point for the analysis of spatial point process data. In this note we extend to the spatio‐temporal setting a method proposed by Baddeley et al. [Statistica Neerlandica (2000) Vol. 54, pp. 329–350] for inhomogeneous spatial point process data, and apply the resulting estimator to data on the spatio‐temporal distribution of human Campylobacter infections in an area of north‐west England.

Background: A simple method called RAPLOA, to rapidly assess what proportion of people in a community are infected with L. loa and hence which communities are at high risk of severe adverse reactions following ivermectin treatment, was developed in Cameroon and Nigeria. The method needed further validation in other geographical and cultural contexts before its application in all endemic countries. The present study was designed to validate RAPLOA in two regions in the North East and South West of the Democratic Republic of Congo. Methods: In each study region, villages were selected from different bio-ecological zones in order to cover a wide range of loiasis endemicity. In each selected community, 80 people above the age of 15 years were interviewed for a history of eye worm (migration of adult L. loa under the conjunctiva of the eye) and parasitologically examined for the presence and intensity of L. loa infection. In total, 8100 individuals from 99 villages were enrolled into the study. Results: The results confirmed the findings of the original RAPLOA study: i) the eye worm phenomenon was well-known in all endemic areas, ii) there was a clear relationship between the prevalence of eye worm history and the prevalence and intensity of L. loa microfilaraemia, and iii) using a threshold of 40%, the prevalence of eye worm history was a sensitive and specific indicator of high-risk communities. Conclusion: Following this successful validation, RAPLOA was recommended for the assessment of loiasis endemicity in areas targeted for ivermectin treatment by lymphatic filariasis and onchocerciasis control programmes.

Background: Loiasis is a major obstacle to ivermectin treatment for onchocerciasis control and lymphatic filariasis elimination in central Africa. In communities with a high level of loiasis endemicity, there is a significant risk of severe adverse reactions to ivermectin treatment. Information on the geographic distribution of loiasis in Africa is urgently needed but available information is limited. The African Programme for Onchocerciasis Control (APOC) undertook large scale mapping of loiasis in 11 potentially endemic countries using a rapid assessment procedure for loiasis (RAPLOA) that uses a simple questionnaire on the history of eye worm. Methodology/Principal Findings: RAPLOA surveys were done in a spatial sample of 4798 villages covering an area of 250063000 km centred on the heartland of loiasis in Africa. The surveys showed high risk levels of loiasis in 10 countries where an estimated 14.4 million people live in high risk areas. There was a strong spatial correlation among RAPLOA data, and kriging was used to produce spatially smoothed contour maps of the interpolated prevalence of eye worm and the predictive probability that the prevalence exceeds 40%. Conclusion/Significance: The contour map of eye worm prevalence provides the first global map of loiasis based on actual survey data. It shows a clear distribution with two zones of hyper endemicity, large areas that are free of loiasis and several borderline or intermediate zones. The surveys detected several previously unknown hyperendemic foci, clarified the distribution of loiasis in the Central African Republic and large parts of the Republic of Congo and the Democratic Republic of Congo for which hardly any information was available, and confirmed known loiasis foci. The new maps of the prevalence of eye worm and the probability that the prevalence exceeds the risk threshold of 40% provide critical information for ivermectin treatment programs among millions of people in Africa.

INTRODUCTION: With COVID-19, there is urgency for policymakers to understand and respond to the health needs of slum communities. Lockdowns for pandemic control have health, social and economic consequences. We consider access to healthcare before and during COVID-19 with those working and living in slum communities. METHODS: In seven slums in Bangladesh, Kenya, Nigeria and Pakistan, we explored stakeholder perspectives and experiences of healthcare access for non-COVID-19 conditions in two periods: pre-COVID-19 and during COVID-19 lockdowns. RESULTS: Between March 2018 and May 2020, we engaged with 860 community leaders, residents, health workers and local authority representatives. Perceived common illnesses in all sites included respiratory, gastric, waterborne and mosquitoborne illnesses and hypertension. Pre-COVID, stakeholders described various preventive, diagnostic and treatment services, including well-used antenatal and immunisation programmes and some screening for hypertension, tuberculosis, HIV and vectorborne disease. In all sites, pharmacists and patent medicine vendors were key providers of treatment and advice for minor illnesses. Mental health services and those addressing gender-based violence were perceived to be limited or unavailable. With COVID-19, a reduction in access to healthcare services was reported in all sites, including preventive services. Cost of healthcare increased while household income reduced. Residents had difficulty reaching healthcare facilities. Fear of being diagnosed with COVID-19 discouraged healthcare seeking. Alleviators included provision of healthcare by phone, pharmacists/drug vendors extending credit and residents receiving philanthropic or government support; these were inconsistent and inadequate. CONCLUSION: Slum residents' ability to seek healthcare for non-COVID-19 conditions has been reduced during lockdowns. To encourage healthcare seeking, clear communication is needed about what is available and whether infection control is in place. Policymakers need ...

Introduction: With COVID-19, there is urgency for policymakers to understand and respond to the health needs of slum communities. Lockdowns for pandemic control have health, social and economic consequences. We consider access to healthcare before and during COVID-19 with those working and living in slum communities. Methods: In seven slums in Bangladesh, Kenya, Nigeria and Pakistan, we explored stakeholder perspectives and experiences of healthcare access for non-COVID-19 conditions in two periods: pre-COVID-19 and during COVID-19 lockdowns. Results: Between March 2018 and May 2020, we engaged with 860 community leaders, residents, health workers and local authority representatives. Perceived common illnesses in all sites included respiratory, gastric, waterborne and mosquitoborne illnesses and hypertension. Pre-COVID, stakeholders described various preventive, diagnostic and treatment services, including well-used antenatal and immunisation programmes and some screening for hypertension, tuberculosis, HIV and vectorborne disease. In all sites, pharmacists and patent medicine vendors were key providers of treatment and advice for minor illnesses. Mental health services and those addressing gender-based violence were perceived to be limited or unavailable. With COVID-19, a reduction in access to healthcare services was reported in all sites, including preventive services. Cost of healthcare increased while household income reduced. Residents had difficulty reaching healthcare facilities. Fear of being diagnosed with COVID-19 discouraged healthcare seeking. Alleviators included provision of healthcare by phone, pharmacists/drug vendors extending credit and residents receiving philanthropic or government support; these were inconsistent and inadequate. Conclusion: Slum residents' ability to seek healthcare for non-COVID-19 conditions has been reduced during lockdowns. To encourage healthcare seeking, clear communication is needed about what is available and whether infection control is in place. Policymakers need to ensure that costs do not escalate and unfairly disadvantage slum communities. Remote consulting to reduce face-to-face contact and provision of mental health and gender-based violence services should be considered.