Le cholera est une maladie diarrhéique aiguë due à la consommation d’eau ou d’aliments contaminés par des souches toxigéniques de Vibrio cholerae. Selon le “paradigme du choléra”, la maladie est provoquée par une exposition à un réservoir environnemental de V. cholerae avec des épidémies directement modulées par des facteurs environnementaux. Cependant, comme divers arguments plaident contre ce dogme, nous avons voulu élucider les mécanismes de la dynamique des épidémies de cholera dans trois foyers situés en Haïti, en République Démocratique du Congo (RDC) et en Afrique de l’Ouest. Nous avons associé une analyse temporo-spatiale des épidémies à une étude génétique des isolats de V. cholerae. En Haïti, nous avons cherché à savoir si les épidémies actuelles étaient dues à des souches toxigéniques de V. cholerae O1 durablement implantées dans l’environnement aquatique. En Afrique de l’Ouest, notre étude a révélé qu’Accra, la capitale du Ghana, était le principal foyer de choléra pour l’ensemble des pays d’Afrique de l’Ouest situés à l’Ouest du Nigeria. Le réseau d’eau d’Accra a probablement joué un rôle dans la propagation rapide de V. cholerae vers la majorité des quartiers de la ville. Les épidémies de choléra ont diffusé vers les autres pays sous la forme de vagues épidémiques et plusieurs épidémies ont été liées à la migration de populations à risque comme certains pêcheurs. En conclusion, notre réflexion globale sur les épidémies de choléra dans ces trois foyers distincts nous donne une vision cohérente des mécanismes d’émergence et de diffusion du choléra. / Cholera is an acute diarrheal disease caused by consumption of water or food contaminated with toxigenic Vibrio cholerae. According to the "cholera paradigm", the disease is contracted by exposure to environmental reservoirs of V. cholerae, with outbreaks driven directly by climatic factors. However, as recent findings argue against this dogma, we aimed to elucidate the dynamics of cholera outbreaks in three global foci: Haiti, Democratic Republic of the Congo (DRC) and West Africa. We combined spatiotemporal analysis of epidemics with genetic assessment of V. cholerae isolates. In Haiti, we assessed whether outbreak re-emergence during the rainy season was due to toxigenic V. cholerae O1 strains that have settled into the aquatic environment. Instead, we found that the re-emergence of outbreaks was likely due to persisting outbreaks during the dry season that were insufficiently controlled, rather than an environmental reservoir of V. cholerae O1. In West Africa, our study revealed that Accra, Ghana was the hotspot of cholera in the entire region of West Africa, west of Nigeria. The Accra water network likely played a role in rapid diffusion of V. cholerae throughout the city. Cholera outbreaks spread from Accra into other countries in a wave-like fashion. Distinct outbreaks were linked via migration of at-risk populations, such as certain fishermen. In conclusion, our global reflection of cholera epidemics in these three distinct foci provides a coherent vision of the mechanisms of cholera emergence and diffusion.

Orientador: Everardo Duarte Nunes / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas / Made available in DSpace on 2018-08-22T07:12:36Z (GMT). No. of bitstreams: 1 Pavanati_CassiaMariane_M.pdf: 4552461 bytes, checksum: 1b0e533a61f66951f4df48cb10427e29 (MD5) Previous issue date: 2013 / Resumo: Este estudo reconstitui através de uma revisão das fontes historiográficas e documentais, a história da saúde, doença e do sanitarismo da cidade de Campinas durante a Primeira República brasileira, do final do século XIX às primeiras décadas do século XX. Este período de significativas transformações no Brasil, não apenas políticas, também modificaram notoriamente as questões referentes à saúde, tanto no país como na cidade de Campinas. Campinas se destacou como produtora agrícola, inicialmente, e mais tarde como centro industrial e comercial. O trabalho ressalta as diversas modificações pelas quais a cidade atravessou durante os sucessivos surtos epidêmicos que assolaram a cidade, principalmente a febre amarela; destaca a implantação e organização das primeiras instituições destinadas ao tratamento da saúde e doença. A reconstituição proveniente da revisão historiográfica compõe um cenário geral sobre a situação sanitária do período, como da estruturação do serviço de saúde na cidade em meio às mudanças políticas, econômicas, sociais e culturais, intrínsecas à Primeira República brasileira / Abstract: This study reproduces through a review of documentary sources and historiography, the history of health, disease and sanitarism city of Campinas in Brazil during the First Republic, the late nineteenth century to the early decades of the twentieth century. This period of significant transformations in Brazil, not just policies also changed markedly issues relating to health, both at home and in the city of Campinas. Campinas excelled as agricultural production, initially, and later as industrial and commercial center. The work highlights the various changes which the city went through during successive epidemics that ravaged the city, especially yellow fever; highlights the organization and deployment of the first institutions for the treatment of health and disease. Reconstitution from the historiographical revision composes a scene on the general health situation of the period, as the structure of the health service in the city amid the political, economic, social and cultural, intrinsic to the First Brazilian Republic / Mestrado / Ciências Sociais em Saúde / Mestra em Saúde Coletiva

No description available.

Historically African Horsesickness (AHS) outbreaks are rare occurrences in the Western Cape Province. The 2004 outbreak was particularly troubling since it followed only five years after the previous outbreak and even before any cases were reported further inland, which is traditionally the source of infection for the southern (non-endemic) parts of the country. Following confirmation of the diagnosis, control measures were immediately instituted and an epidemiological investigation was initiated. The investigation revealed, inter alia, that serological profiles of case horses were inconsistent. A case was subsequently defined as a horse showing typical symptoms of AHS and from which virus could be isolated. The disease pattern for both the 2004 and 1999 outbreaks can be classified as sporadic epidemics. This type of epidemic pattern is to be expected in a vector borne disease and it is typical in a disease situation where some of the animals are immune. The temporal pattern revealed that the level of immunity in the equine population of the affected area was higher during the 2004 outbreak than during the 1999 outbreak. In addition, it showed a clustering of cases during the initial stages of both the 2004 and 1999 outbreaks. This illustrated the efficacy of the control measures (including movement and vector control), which was instituted immediately after the diagnosis of the first case. The analysis of the spatial pattern during both the 2004 and 1999 outbreaks identified the Eerste-river-valley as a high-risk area for the outbreak of AHS in the surveillance zone. The population pattern during the 2004 outbreak illustrated that the risk of dying of AHS was higher in horses of 5 years and younger (p<0.10). It was shown that vaccination and stabling offers the best protection against the risk of dying as a result of AHS infection in an exposed population (p<0.05). A questionnaire survey was conducted as part of the epidemiological investigation and it revealed that only 12.4% of equine holdings in the affected area practiced vector control, while a high percentage of horses (69.6%) were protected by means of vaccination, which impacts negatively on the purpose of a surveillance zone. The number of Culicoides imicola midges in the area where the outbreak was detected was extremely high, constituting 94.6% of the Culicoides midge population. This is comparable with the 1999 outbreak when 96.0% of the midges collected were identified as C. imicola. However, during a similar survey in 1996, C. imicola comprised only 11.3% of the population (Neville et al. 1988, Venter, G., personal communication 2004). Furthermore, the outbreak was detected even before significant rainfall was recorded in the region and transmission occurred at average minimum temperatures below 15 °C. The virus responsible for the 2004 outbreak was typed as AHS serotype 1, while AHS serotype 7 was identified as the cause of the 1999 outbreak. The source of the infection in the 1999 outbreak was the illegal movement of two horses from the Free State Province in the infected zone into the surveillance zone. Although no absolute proof could be obtained, there is strong evidence that the source of the 2004 outbreak was again the movement of horses, this time from Namibia, accentuating that horse movements constitutes the highest risk to the integrity of the free zone. Since the ability to control an outbreak successfully is directly dependant on rapid detection and given the large number of vaccinated horses as a result of the outbreaks and the AHS movement control policy, amendments to the export policy and legislation are recommended. AHS outbreaks in the control area of South Africa cause substantial financial loss to the horse industry and the controlling authorities. / Dissertation (MSc (Veterinary Science))--University of Pretoria, 2006. / Production Animal Studies / unrestricted

When an outbreak of an infectious disease occurs, public health officials need to understand the dynamics of disease transmission in order to launch an effective response. Two quantities that are often used to describe transmission are the basic reproductive number and the distribution of the serial interval. The basic reproductive number, R0, is the average number of secondary cases a primary case will infect, assuming a completely susceptible population. The serial interval (SI) provides a measure of temporality, and is defined as the time between symptom onset between a primary case and its secondary case. Investigators typically collect outbreak data in the form of an epidemic curve that displays the number of cases by each day (or other time scale) of the outbreak. Occasionally the epidemic curve data is more expansive and includes demographic or other information. A contact trace sample may also be collected, which is based on a sample of the cases that have their contact patterns traced to determine the timing and sequence of transmission. In addition, numerous large scale social mixing surveys have been administered in recent years to collect information about contact patterns and infection rates among different age groups. These are readily available and are sometimes used to account for population heterogeneity. In this dissertation, we modify the methods presented in White and Pagano (2008) to account for additional data beyond the epidemic curve to estimate R0 and SI. We present two approaches that incorporate these data through the use of a Bayesian framework. First, we consider informing the prior distribution of the SI with contact trace data and examine implications of combining data that are in conflict. The second approach extends the first approach to account for heterogeneity in the estimation of R0. We derive a modification to the White and Pagano likelihood function and utilize social mixing surveys to inform the prior distributions of R0. Both approaches are assessed through a simulation study and are compared to alternative approaches, and are applied to real outbreak data from the 2003 SARS outbreak in Hong Kong and Singapore, and the influenza A(H1N1)2009pdm outbreak in South Africa.

Aging has long been associated with a (i) systematic bias in both attention and in memory towards positive stimuli compared with negative, and (ii) a gradual increase in self-reported positive affect and decrease in negative affect in daily life. The findings are considered to be paradoxical, because as people get older, the neural mechanisms responsible for cognitive functioning undergo gradual decline in structure and function. This dissertation aims to break down the mechanisms of aging that allow for the age-related changes in emotion to prevail in the midst of other ongoing aging processes. Here, I present three papers that address age-related changes in emotional experience. Study 1 showed that age predicted feeling more positive and less negative when faced with a pandemic that disproportionality impacted older adults. Study 2 showed that while younger adults are better than older adults at regulating negative images, all participants rely on similar brain regions for accomplishing the same regulatory goals. Study 3 showed that when given the explicit goal to up or down-regulate positivity, older adults do not have an advantage over younger adults. One way to explain these results is that there are age-related distinctions between the way participants behave in lab-based studies and when they are observed in daily life, which account for inconsistencies between my three studies.

The main goal of this project is to investigate the behaviors of parameters used when modeling an epidemic. A stochastic SIHDRe model is used to simulate how an epidemic evolves over time. The SIHDRe model has nine parameters, and this project focuses on the infection rate (β) and the fraction of infections leading to deaths (FID), with all other parameters being considered known. Both parameters are time dependent. To estimate the two chosen parameters, this project uses synthetic data so that comparisons between estimations with true parameters are possible. A dynamic optimization procedure inspired by Model Predictive Control is utilized for the predictions. Using synthesized data from hospitalizations and deaths, a cost function is minimized to obtain estimations of the parameters. Only a subset of the time span, called a window, is considered for every parameter optimization. The parameters within the window are optimized and the window then moves forward in time defined by a time step until the parameters are optimized over the whole time span. To obtain error estimations of the parameters, synthetic bootstrapping is used, using optimized parameters to simulate new epidemics of which the parameters are optimized. The square difference between the new estimations compared to the original estimations can be used to obtain the standard deviation of the estimated parameters. This project also discusses how regularization parameters within the cost functions are chosen so that the estimated parameters will be most similar to the real parameter values, and end-of-data effects, i.e. increased uncertainty towards the end of a window, is also discussed. / Projektet undersöker hur olika parametrar till en epidemisk modell kan skattas. En stokastisk SIHDRe modell (Susceptible, Infected, Hospitalizalized, Dead, Recovered) används för att simulera hur en epidemi utvecklas över tid. SIDHRe modellen delar in populationen i olika grupper baserat på hur epidemin har påverkat dem, till exempel om de har blivit smittade eller om de har hamnat på sjukhus på grund av sjukdomen. Personer kan flyttas mellan olika grupper beroende på en rad parametrar samt storleken på de olika grupperna. Detta projekt fokuserar på att skatta två parameterar: β, som påverkar hur personer med risk för infektion blir smittade, samt FID som påverkar hur många infekterade som dör av sjukdomen. Modellen har nio parametrar totalt och alla andra parametrar anses kända. Projektet använder syntetisk data, som gör det möjligt att jämföra skattningar av parametrarna med deras sanna värden. Båda okända parametrarna är tidsberoende. För att bestämma parametervärdena används en dynamisk optimiseringsmetod. Data från antal individer inlagda på sjukhus samt antal döda anses känt och kan användas för att minimera en kostfunktion som har de okända parametrarna som inmatningsvärden genom att ändra dessa. Tidsspannet begränsas till en mindre del, det sägs att man ser ett fönster av hela tidsspannet. Fönstret startar vid den första tidspunkten och kostfunktionen minimiseras för inmatningsvärden inom fönstret. När detta är gjort flyttas fönstret ett kort tidsteg fram i tiden och optimiseringsprocessen återupprepas tills fönstret når slutet av hela tidsserien och alla parametervärden har uppskattats. Dessa skattade parametervärden kan sen jämföras med de sanna värdena. För att kunna uppskatta felet när parametervärdena bestäms används en metod kallad ”Synthetic Bootstrap”. Grundidén är att parameterna uppskattas en gång ochdenna uppskattning används sen som inmatningsvärde till epidemimodellen. Nya epidemier simuleras och baserat på dessa simuleringar, kan nya parametervärden estimeras. Dessa kommer att skilja i värde på grund av att modellen är stokastisk. De nya uppskattningarna jämförs sedan med de första uppskattningarna och en uppfattning om skillnaden mellan dessa kan sedan beskrivas som en standardavvikelse mellan de nya skattningarna och den första skattningen. Projektet diskuterar också val av olika regulariseringsparametrar för kostfunktionen. Dessa kontrollerar hur mycket de uppskattade värdena kan ändras från tidpunkt till tidpunkt genom att ett stort värde minskar möjliga ändringar och ett litet värde ökar dem. Ett fenomen som kallas ”end-of-data effects” diskuteras också och handlar om att osäkerheten växer i ett fönster ju längre in i fönstret man är.

No description available.

Seasonal and non-seasonal Susceptible-Exposed-Infective-Recovered-Susceptible (SEIRS) models are formulated and analyzed. It is proved that the disease-free steady state of the non-seasonal model is locally asymptotically stable if Rv < 1, and disease invades if Rv > 1. For the seasonal SEIRS model, it is shown that the disease-free periodic solution is locally asymptotically stable when R̅v < 1, and I(t) is persistent with sustained oscillations when R̅v > 1. Numerical simulations indicate that the orbit representing I(t) decays when R̅v < 1 < Rv. The seasonal SEIRS model with routine and pulse vaccination is simulated, and results depict an unsustained decrease in the maximum of prevalence of infectives upon the introduction of routine vaccination and a sustained decrease as pulse vaccination is introduced in the population. Mortality data of pneumonia and influenza is collected and analyzed. A decomposition of the data is analyzed, trend and seasonality effects ascertained, and a forecasting strategy proposed.

Mathematical models of disease spreading are a key factor of ensuring that we are prepared to deal with the next epidemic. They allow us to predict how an infection will spread throughout a population, thereby allowing us to make intelligent choices when attempting to contain the disease. Whether due to a lack of empirical data, a lack of computational power, a lack of biological understanding, or some combination thereof, traditional models must make sweeping assumptions about the behavior of a population during an epidemic. In this thesis, we implement granular epidemic simulations using a rich social network constructed from real-world interactions. We develop computational models for three diseases, and we use these simulations to demonstrate the effects of twelve potential intervention strategies, both before and during a hypothetical epidemic. We show how representing a population as a temporal graph and applying existing graph metrics can lead to more effective interventions.