Rapid decrease of malaria morbidity following the introduction of community-based monitoring in a rural area of central Vietnam

<p>Abstract</p> <p>Background</p> <p>Despite a successful control programme, malaria has not completely disappeared in Vietnam; it remains endemic in remote areas of central Vietnam, where standard control activities seem to be less effective. The evolution of malaria prevalence and incidence over two and half years in a rural area of central Vietnam, after the introduction of community-based monitoring of malaria cases, is presented.</p> <p>Methods</p> <p>After a complete census, six cross-sectional surveys and passive detection of malaria cases (by village and commune health workers using rapid diagnostic tests) were carried out between March 2004 and December 2006 in Ninh-Thuan province, in a population of about 10,000 individuals. The prevalence of malaria infection and the incidence of clinical cases were estimated.</p> <p>Results</p> <p>Malaria prevalence significantly decreased from 13.6% (281/2,068) in December 2004 to 4.0% (80/2,019) in December 2006. <it>Plasmodium falciparum </it>and <it>Plasmodium vivax </it>were the most common infections with few <it>Plasmodium malariae </it>mono-infections and some mixed infections. During the study period, malaria incidence decreased by more than 50%, from 25.7/1,000 population at risk in the second half of 2004 to 12.3/1,000 in the second half of 2006. The incidence showed seasonal variations, with a yearly peak between June and December, except in 2006 when the peak observed in the previous years did not occur.</p> <p>Conclusion</p> <p>Over a 2.5-year follow-up period, malaria prevalence and incidence decreased by more than 70% and 50%, respectively. Possibly, this could be attributed to the setting up of a passive case detection system based on village health workers, indicating that a major impact on the malaria burden can be obtained whenever prompt diagnosis and adequate treatment are available.</p

Sero-epidemiological evaluation of changes in Plasmodium falciparum and Plasmodium vivax transmission patterns over the rainy season in Cambodia

<p>Abstract</p> <p>Background</p> <p>In Cambodia, malaria transmission is low and most cases occur in forested areas. Sero-epidemiological techniques can be used to identify both areas of ongoing transmission and high-risk groups to be targeted by control interventions. This study utilizes repeated cross-sectional data to assess the risk of being malaria sero-positive at two consecutive time points during the rainy season and investigates who is most likely to sero-convert over the transmission season.</p> <p>Methods</p> <p>In 2005, two cross-sectional surveys, one in the middle and the other at the end of the malaria transmission season, were carried out in two ecologically distinct regions in Cambodia. Parasitological and serological data were collected in four districts. Antibodies to <it>Plasmodium falciparum </it>Glutamate Rich Protein (GLURP) and <it>Plasmodium vivax </it>Merozoite Surface Protein-1₁₉(MSP-1₁₉) were detected using Enzyme Linked Immunosorbent Assay (ELISA). The force of infection was estimated using a simple catalytic model fitted using maximum likelihood methods. Risks for sero-converting during the rainy season were analysed using the Classification and Regression Tree (CART) method.</p> <p>Results</p> <p>A total of 804 individuals participating in both surveys were analysed. The overall parasite prevalence was low (4.6% and 2.0% for <it>P. falciparum </it>and 7.9% and 6.0% for <it>P. vivax </it>in August and November respectively). <it>P. falciparum </it>force of infection was higher in the eastern region and increased between August and November, whilst <it>P. vivax </it>force of infection was higher in the western region and remained similar in both surveys. In the western region, malaria transmission changed very little across the season (for both species). CART analysis for <it>P. falciparum </it>in the east highlighted age, ethnicity, village of residence and forest work as important predictors for malaria exposure during the rainy season. Adults were more likely to increase their antibody responses to <it>P. falciparum </it>during the transmission season than children, whilst members of the Charay ethnic group demonstrated the largest increases.</p> <p>Discussion</p> <p>In areas of low transmission intensity, such as in Cambodia, the analysis of longitudinal serological data enables a sensitive evaluation of transmission dynamics. Consecutive serological surveys allow an insight into spatio-temporal patterns of malaria transmission. The use of CART enabled multiple interactions to be accounted for simultaneously and permitted risk factors for exposure to be clearly identified.</p

Propagule predators in Kenyan mangroves and their possible effect on regeneration

info:eu-repo/semantics/publishe

Can redox state in mangroves explain mangrove vegetation structure ?

info:eu-repo/semantics/nonPublishe

Mangrove vegetation dynamics: how to look into the past ?

info:eu-repo/semantics/nonPublishe

The Mantel-Haenszel Procedure Revisited:Models and Generalizations

<p>Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented.</p>