The neglected tropical diseases of Latin America and the Caribbean: a review of disease burden and distribution and a roadmap for control and elimination.

The neglected tropical diseases (NTDs) represent some of the most common infections of the poorest people living in the Latin American and Caribbean region (LAC). Because they primarily afflict the disenfranchised poor as well as selected indigenous populations and people of African descent, the NTDs in LAC are largely forgotten diseases even though their collective disease burden may exceed better known conditions such as of HIV/AIDS, tuberculosis, or malaria. Based on their prevalence and healthy life years lost from disability, hookworm infection, other soil-transmitted helminth infections, and Chagas disease are the most important NTDs in LAC, followed by dengue, schistosomiasis, leishmaniasis, trachoma, leprosy, and lymphatic filariasis. On the other hand, for some important NTDs, such as leptospirosis and cysticercosis, complete disease burden estimates are not available. The NTDs in LAC geographically concentrate in 11 different sub-regions, each with a distinctive human and environmental ecology. In the coming years, schistosomiasis could be eliminated in the Caribbean and transmission of lymphatic filariasis and onchocerciasis could be eliminated in Latin America. However, the highest disease burden NTDs, such as Chagas disease, soil-transmitted helminth infections, and hookworm and schistosomiasis co-infections, may first require scale-up of existing resources or the development of new control tools in order to achieve control or elimination. Ultimately, the roadmap for the control and elimination of the more widespread NTDs will require an inter-sectoral approach that bridges public health, social services, and environmental interventions.

[Mutilating acrodystrophic neuropathy of alcoholic origin in the French West Indies]. / Acropathie ulcéromutilante d'origine alcoolique aux Antilles.

Among principal causes of acrodystrophic neuropathy-ie, leprosy, diabetes, amyloid neuropathy, hereditary sensory neuropathies-alcoholism is controversial since first descriptions (Bureau et al, 1957) incriminating heavy drinking. This retrospective review of 38 cases occurring in West-Indian rhum abusers, tends however to confirm its etiologic role. Patients present with three non specific signs or symptoms of the lower extremities: anaesthetic foot, plantar ulcers, and chronic, indolent, mutilating arthropathies. Motor function is spared. Male gender, massive (> or = 150 g pure alcohol daily) and prolonged (> or = 12 years) rhum intake, hygiene deficiency, poverty and social distress, exposition to repeated foot microtrauma and a protracted, non fatal, but disabling course leading to amputation, are the main features of this syndrome. The pathophysiology is poorly documented, and many questions remain unanswered including a genetic predisposition or a particular neuro-toxicity of West Indian rhum. However, the clinical and epidemiologic data presented here favour the concept of an "alcoholic foot" or true alcoholic acrodystrophic neuropathy, quite different from the most common sensory-motor form.

A time-dependent logistic hazard function for modeling variable age of onset in analysis of familial diseases.

The paper presents an extension of the regressive logistic models proposed by Bonney [Biometrics 42:611-625, 1986], to address the problems of variable age-of-onset and time-dependent covariates in analysis of familial diseases. This goal is achieved by using failure time data analysis methods, and partitioning the time of follow up in K mutually exclusive intervals. The conditional probability of being affected within the kth interval (k = 1...K) given not affected before represents the hazard function in this discrete formulation. A logistic model is used to specify a regression relationship between this hazard function and a set of explanatory variables including genotype, phenotypes of ancestors, and other covariates which can be time dependent. The probability that a given person either becomes affected within the kth interval (i.e., interval k includes age of onset of the person) or remains unaffected by the end of the kth interval (i.e., interval k includes age at examination of the person) are derived from the general results of failure time data analysis and used for the likelihood formulation. This proposed approach can be used in any genetic segregation and linkage analysis in which a penetrance function needs to be defined. Application of the method to familial leprosy data leads to results consistent with our previous analysis performed using the unified mixed model [Abel and Demenais, Am J Hum Genet 42:256-266, 1988], i.e., the presence of a recessive major gene controlling susceptibility to leprosy. Furthermore, a simulation study shows the capability of the new model to detect major gene effects and to provide accurate parameter estimates in a situation of complete ascertainment.

A time-dependent logistic hazard function for modeling variable age of onset in analysis of familial diseases

This paper presents an extension of the regressive logistic model proposed by Bonney [Biometrics 42:611-625, 1986], to address the problems of variable age-of-onset and time-dependent covariates in analysis of familial diseases. The goal is achieved by using failure time data analysis methods, and partitioning the time of follow up in K mutually exclusive intervals. The conditional probability of being affected within the Kth interval (K=1...K) given not affected before represents the hazaard function in this discrete formulation. A logistic model is used to specify a regression relationship between this hazard function and a set of explanatory variables including genotype, phenotype of ancestors and other covariates which can be time independent. The probability that a given person either becomes affected within the Kth interval (ie. interval K includes age of onset of the person) or remains unaffected by the end of the Kth interval (ie. interval K includes age at examination of the person) are derived from the general result of failure time data analysis and used for the likelihood formulation. This proposed approach can be used in any genetic segregation and linkage analysis in which a penetrance function needs to be defined. Application of the method to familial leprosy data leads to results consistent with our previous analysis performed using the unified mixed model [Abel and Demenias, Am J Hum Genet 42:256-266, 1988], ie. the presence of a recessive major gene controlling susceptibility to leprosy. Furthermore, a simulation study shows the capability of the new method to detect major gene effects and to provide accurate parameter estimates in a situation of complete ascertainment. (AU)