En Afrique tropicale, là où le paludisme est fortement endémique, la plupart des individus sont semi-immuns et les infections asymptomatiques sont très répandues. Ainsi la détection de parasites dans le sang de malades fébriles n'est pas un critère suffisant pour distinguer le paludisme des autres causes de fièvre. A Dielmo, un village du Sénégal d'environ 500 habitants en 2010, un suivi épidémiologique continu très étroit du paludisme a débuté en 1990. Dans ce village où la transmission est pérenne, la mise en place de moyens de lutte et de prévention contre le paludisme de plus en plus efficaces a profondément transformé l'épidémiologie du paludisme. Dans ce travail, nous analysons l'impact de ces interventions sur les prévalences parasitaires, les densités parasitaires et les critères diagnostiques du paludisme et nous mesurons l'évolution du paludisme clinique à Plasmodium falciparum, P. malariae et P. ovale de juin 1990 à décembre 2010. Les données parasitologiques et cliniques ont été analysées par régression logistique à effet aléatoire pour étudier la relation entre les densités parasitaires et le risque de fièvre. Les prévalences parasitaires des trois espèces plasmodiales ont considérablement diminué lors de l'abandon de la chloroquine en traitement de première ligne et de son remplacement par des combinaisons thérapeutiques, puis sont devenues presque nulles après la mise en place de moustiquaires imprégnées d'insecticides à longue durée d'action. Les seuils pyrogéniques calculés nous ont permis de mesurer la densité d'incidence des accès palustres et d'étudier l'impact des mesures de lutte sur la morbidité palustre dans la population. / In tropical Africa, where malaria is highly endemic, most people are semi-immune and asymptomatic infections are widespread. Thus, the detection of malaria parasites in the blood of febrile patients is not a sufficient criterion for distinguishing malaria from other causes of fever. In Dielmo, a Senegalese village of about 500 inhabitants in 2010, a very closely continuous epidemiological monitoring of malaria began in 1990. In this village where the transmission is perennial, the establishment of more effective means of control and prevention against malaria have profoundly changed the epidemiology of malaria. In this work, we analyze the impact of these interventions on the parasite prevalences, the parasite densities and the malaria diagnostic criteria and we measure the evolution of Plasmodium falciparum, P. malariae and P. ovale clinical malaria from June 1990 to December 2010 in Dielmo. Parasitological and clinical data are analyzed in a random effect logistic regression to investigate the relationship between parasite density and fever risk. The prevalence of the three Plasmodium species decreased dramatically with the abandonment of chloroquine as first line treatment and his replacing with the combination therapies and became almost zero after the introduction of long lasting insecticidal nets. Pyrogenic thresholds calculated enabled us to measure the incidence density of malaria and to study the impact of intervention methods on malaria morbidity in the population.

Pas de résumé en français / Malaria is a devastating global health problem that affected 219 million people and caused 660,000 deaths in 2010. Inaccurate estimation of the level of infection may have adverse clinical and therapeutic implications for patients, and for epidemiological endpoint measurements. The level of infection, expressed as the parasite density (PD), is classically defined as the number of asexual parasites relative to a microliter of blood. Microscopy of Giemsa-stained thick blood smears (TBSs) is the gold standard for parasite enumeration. Parasites are counted in a predetermined number of high-power fields (HPFs) or against a fixed number of leukocytes. PD estimation methods usually involve threshold values; either the number of leukocytes counted or the number of HPFs read. Most of these methods assume that (1) the distribution of the thickness of the TBS, and hence the distribution of parasites and leukocytes within the TBS, is homogeneous; and that (2) parasites and leukocytes are evenly distributed in TBSs, and thus can be modeled through a Poisson-distribution. The violation of these assumptions commonly results in overdispersion. Firstly, we studied the statistical properties (mean error, coefficient of variation, false negative rates) of PD estimators of commonly used threshold-based counting techniques and assessed the influence of the thresholds on the cost-effectiveness of these methods. Secondly, we constituted and published the first dataset on parasite and leukocyte counts per HPF. Two sources of overdispersion in data were investigated: latent heterogeneity and spatial dependence. We accounted for unobserved heterogeneity in data by considering more flexible models that allow for overdispersion. Of particular interest were the negative binomial model (NB) and mixture models. The dependent structure in data was modeled with hidden Markov models (HMMs). We found evidence that assumptions (1) and (2) are inconsistent with parasite and leukocyte distributions. The NB-HMM is the closest model to the unknown distribution that generates the data. Finally, we devised a reduced reading procedure of the PD that aims to a better operational optimization and a practical assessing of the heterogeneity in the distribution of parasites and leukocytes in TBSs. A patent application process has been launched and a prototype development of the counter is in process.

Malaria is a devastating global health problem that affected 219 million people and caused 660,000 deaths in 2010. Inaccurate estimation of the level of infection may have adverse clinical and therapeutic implications for patients, and for epidemiological endpoint measurements. The level of infection, expressed as the parasite density (PD), is classically defined as the number of asexual parasites relative to a microliter of blood. Microscopy of Giemsa-stained thick blood smears (TBSs) is the gold standard for parasite enumeration. Parasites are counted in a predetermined number of high-power fields (HPFs) or against a fixed number of leukocytes. PD estimation methods usually involve threshold values; either the number of leukocytes counted or the number of HPFs read. Most of these methods assume that (1) the distribution of the thickness of the TBS, and hence the distribution of parasites and leukocytes within the TBS, is homogeneous; and that (2) parasites and leukocytes are evenly distributed in TBSs, and thus can be modeled through a Poisson-distribution. The violation of these assumptions commonly results in overdispersion. Firstly, we studied the statistical properties (mean error, coefficient of variation, false negative rates) of PD estimators of commonly used threshold-based counting techniques and assessed the influence of the thresholds on the cost-effectiveness of these methods. Secondly, we constituted and published the first dataset on parasite and leukocyte counts per HPF. Two sources of overdispersion in data were investigated: latent heterogeneity and spatial dependence. We accounted for unobserved heterogeneity in data by considering more flexible models that allow for overdispersion. Of particular interest were the negative binomial model (NB) and mixture models. The dependent structure in data was modeled with hidden Markov models (HMMs). We found evidence that assumptions (1) and (2) are inconsistent with parasite and leukocyte distributions. The NB-HMM is the closest model to the unknown distribution that generates the data. Finally, we devised a reduced reading procedure of the PD that aims to a better operational optimization and a practical assessing of the heterogeneity in the distribution of parasites and leukocytes in TBSs. A patent application process has been launched and a prototype development of the counter is in process.