11 research outputs found
Complications postopératoires dans le service de chirurgie de l'Hôpital Fousseyni DAOU de Kayes.
No full textLes complications postopératoires représentent des indicateurs importants pour la qualité des soins en chirurgie. Objectifs: Les objectifs étaient de déterminer la fréquence, d'identifier les CPO, les facteurs de risque, de décrire les aspects thérapeutique et diagnostique. Méthodologie: Il s'agit d'une étude prospective réalisée dans le service de chirurgie générale de l'Hôpital Fousseyni DAOU de Kayes du 1er Avril au 31 Mars 2011. Elle a porté sur tous les malades âgés d'au moins 15 ans, opérés et hospitalisés, au moins 3 jours et qui ont présenté des complications pendant les 30 jours postopératoires. Les malades âgés de moins de 15 ans, ou opérés en ambulatoire, n'ont pas été retenus. Résultats: Nous avons colligé 290 patients parmi lesquels 182 (62,8 p.100 ) étaient des hommes et 108 (37,2 p.100 ) des femmes, soit un sex-ratio égal 1,7. L'âge moyen a été de 41,67 ans, avec des extrêmes variant entre 15 et 75 ans. Les principaux diagnostics initiaux étaient: Les appendicites aiguës, les péritonites, les occlusions sur brides, les hernies inguinales étranglées, les hémorroides, le plastron appendiculaire refroidi, le volvulus sigmoide, l'hémopéritoine hémodynamiquement instable, la hernie inguinale non compliquée et l'éventration. Les urgences ont représenté 44,5 p.100 (n égal 129) des interventions avec 72,3 p.100 de Complications Postopératoires (CPO). Nous avons enregistré 22,4 p.100 (n égal 65) CPO dans un délai d'apparition moyen de 3 jours. Les infections nosocomiales ont représenté 61,5 p.100 (n égal 40) des CPO dont l'infection du site opératoire 47,7 p.100 (n égal 31), les infections urinaire et pulmonaire respectivement 1,5 p.100 et 4,6 p.100 (n égal 1 et n égal 3), la péritonite 3,0 p.100 (n égal 2). Les autres complications ont été: L'éviscération 3,1 p.100 (n égal 2), les fistules digestives externes, les hématomes scrotaux, l'hémorragie de la paroi 4,6 p.100 (n égal 3) chacun, les occlusions intestinales 3,1 p.100 (n égal 2) et une mortalité de 23,1 p.100 (n égal 15). La prise en charge des CPO a été chirurgicale dans 61,4 p.100 et médicale 15,3 p.100 . Leur survenue a prolongé le séjour hospitalier (27,9 jours contre 13,3 jours) et a majoré le coût moyen de prise en charge de 51,2 p.100 . L'Indice de Mortalité Abaissé par une Gestion Efficiente des complications (IMAGE) calculé par rapport aux décès inattendus a été de 94 p.100 . Conclusion: l'urgence, l'âge, le score ASA supérieur ou égal III, les classes sales d'Altemeir, le score de NNISS ont été les facteurs favorisants des complications postopératoires
Brulures corporelles à l'Hôpital Fousseyni Daou de Kayes
No full textLa brûlure est une pathologie très fréquente avec une mortalité très élevée surtout en Afrique, spécialement dans les pays en voie de développement où la prise en charge des brûlés demeure un véritable challenge. OBJECTIFS : Déterminer la fréquence hospitalière ; -Identifier les facteurs étiologiques des brûlures ; -Décrire les aspects cliniques et para-cliniques des brûlures ; -Analyser les résultats du traitement. METHODOLOGIE : Il s'agit d'une étude prospective et descriptive allant du Décembre 2016 au Décembre 2017 portant sur les brûlures ayant nécessité une hospitalisation dans le service de chirurgie général de l'hôpital Fousseyni DAOU. RESULTATS : Nous avons recensé 55 patients brûlés entre le Décembre 2016 et le Décembre 2017. Le sexe masculin était le plus touché dans 50,9 p.100 des cas contre 49,1 p.100 de femme. La moyenne d'âge était de 21,27 plus ou moins 19,44 ans. Les brûlures étaient thermiques dans 100 p.100 des cas, la flamme était l'agent causal dominant avec 49,1 p.100 . La moyenne de surface corporelle brulée était de 24,44 plus ou moins 20,76 p.100 . Nous avons observé respectivement une fréquence élevée du deuxième degré profond à 50,9 p.100 suivie du deuxième degré superficiel à 38,2 p.100 et le troisième degré à 10,9 p.100 . La durée moyenne d'hospitalisation était de 15,89 jours plus ou moins 10,87 avec des extrêmes de 6 et 50 jours. L'anémie et la dénutrition ont été les complications les plus fréquentes. Facteur prédictif de la mortalité, un score de Baux supérieur à 100 était considéré comme fatal, nous avons eu 14,5 p.100 des cas supérieur à 100. L'âge, la SCB, la profondeur de la brûlure, l'infection, la septicémie et la durée d'hospitalisation sont les facteurs pronostics. La mortalité globale était estimée à 30,9 p.100 de l'effectif. CONCLUSION : Une prise en charge rapide et adaptée à la gravité des lésions est le seul garant d'une survie aux dépens des séquelles fonctionnelles parfois lourdes limitant la réinsertion sociale
Bayesian variable selection in modelling geographical heterogeneity in malaria transmission from sparse data : an application to Nouna Health and Demographic Surveillance System (HDSS) data, Burkina Faso
No full textQuantification of malaria heterogeneity is very challenging, partly because of the underlying characteristics of mosquitoes and also because malaria is an environmentally driven disease. Furthermore, in order to assess the spatial and seasonal variability in malaria transmission, vector data need to be collected repeatedly over time (at fixed geographical locations). Measurements collected at locations close to each other and over time tend to be correlated because of common exposures such as environmental or climatic conditions. Non- spatial statistical methods, when applied to analyze such data, may lead to biased estimates. We developed rigorous methods for analyzing sparse and spatially correlated data. We applied Bayesian variable selection to identify the most important predictors as well as the elapsing time between climate suitability and changes in entomological indices.; Bayesian geostatistical zero-inflated binomial and negative binomial models including harmonic seasonal terms, temporal trends and climatic remotely sensed proxies were applied to assess spatio-temporal variation of sporozoite rate and mosquito density in the study area. Bayesian variable selection was employed to determine the most important climatic predictors and elapsing (lag) time between climatic suitability and malaria transmission. Bayesian kriging was used to predict mosquito density and sporozoite rate at unsampled locations. These estimates were converted to covariate and season-adjusted maps of entomological inoculation rates. Models were fitted using Markov chain Monte Carlo simulation. The results show that Anophele. gambiae is the most predominant vector (79.29%) and is more rain-dependant than its sibling Anophele. funestus (20.71%). Variable selection suggests that the two species react differently to different climatic conditions. Prediction maps of entomological inoculation rate (EIR) depict a strong spatial and temporal heterogeneity in malaria transmission risk despite the relatively small geographical extend of the study area. CONCLUSION: Malaria transmission is very heterogeneous over the study area. The EIR maps clearly depict a strong spatial and temporal heterogeneity despite the relatively small geographical extend of the study area. Model based estimates of transmission can be used to identify high transmission areas in order to prioritise interventions and support research in malaria epidemiology
Distribution of malaria exposure in endemic countries in Africa considering country levels of effective treatment
No full textMalaria prevalence, clinical incidence, treatment, and transmission rates are dynamically interrelated. Prevalence is often considered a measure of malaria transmission, but treatment of clinical malaria reduces prevalence, and consequently also infectiousness to the mosquito vector and onward transmission. The impact of the frequency of treatment on prevalence in a population is generally not considered. This can lead to potential underestimation of malaria exposure in settings with good health systems. Furthermore, these dynamical relationships between prevalence, treatment, and transmission have not generally been taken into account in estimates of burden.; Using prevalence as an input, estimates of disease incidence and transmission [as the distribution of the entomological inoculation rate (EIR)] for Plasmodium falciparum have now been made for 43 countries in Africa using both empirical relationships (that do not allow for treatment) and OpenMalaria dynamic micro-simulation models (that explicitly include the effects of treatment). For each estimate, prevalence inputs were taken from geo-statistical models fitted for the year 2010 by the Malaria Atlas Project to all available observed prevalence data. National level estimates of the effectiveness of case management in treating clinical attacks were used as inputs to the estimation of both EIR and disease incidence by the dynamic models.; When coverage of effective treatment is taken into account, higher country level estimates of average EIR and thus higher disease burden, are obtained for a given prevalence level, especially where access to treatment is high, and prevalence relatively low. These methods provide a unified framework for comparison of both the immediate and longer-term impacts of case management and of preventive interventions
Assessing malaria attributed mortality in west and southern Africa
No full textMalaria has persistently remained a serious health and socio-economic problem in developing nations particularly in Sub-Saharan Africa (SSA). There are approximately 500 million cases of malaria each year and close to one million deaths occurring mainly among children under five years. Developing countries spend a reasonable proportion of their gross domestic product (GDP) on malaria which in the end hinders their levels of development.
World Health Organizations (WHO) and partners through the Roll Back Malaria initiative (RBM) have targeted vector control, health promotion and case management (using rapid diagnostic tests and treatment with Artemisinin combination therapy) in order reduce malaria morbidity and mortality cases. Since 2002, funds for promoting malaria control activities have increased exponentially in SSA. Major donors include presidential malaria initiative (PMI) and Global fund to fight AIDS, tuberculosis and malaria (GFATM). Countries which have scaled up the recommended malaria control strategies such as insecticides-treat net (ITN) and treatment of confirmed cases have reported a decline in both morbidity and mortality especially among children. However, these statistics are based on health facilities data and yet in most developing countries many deaths occur at home and are never recorded due to inefficient vital registration systems. Monitoring the progress of such interventions requires reliable sources of data on both the transmission and infection outcome.
In malaria endemic areas, people acquire natural immunity during the early years of their life after getting exposed to repeated infections. This is observed from the reductions in the number of severe malaria-related morbidity and mortality cases especially in children >5 years. Due to the current undertakings that are aimed at reducing malaria exposure, there are concerns about shifting the disease burden to older children but the required to data to monitor this are not readily available in SSA. Low income countries have resorted to health and demographic surveillance systems (HDSS) to monitor routinely population changes and health outcomes within a defined geographical area.
In 2000, the INDEPTH, a network of HDSS integrated the Malaria Transmission Intensity and Mortality Burden Across Africa (MTIMBA) project into selected sites’ routine activities in order to assess the transmission-malaria mortality relationship taking into account the current interventions. Mortality data and other demographic characteristics were extracted from routinely collected HDSS databases. The entomological data were collected every fortnight from randomly sampled compounds over the 3 years MTIMBA period.
The MTIMBA project generated large geostatistical data that are correlated in space and time. Furthermore, the project captured longitudinal mosquito data that were characterized by many zeros especially during the dry periods. The zeros are due empty traps from a compound or when all the captured mosquitoes are not infectious. Appropriate data analysis therefore should apply models that account for spatial-temporal correlation and the excess zeros in order to avoid over or underestimation of parameters. Zero-inflated geostatistical models account for spatial-temporal correlation by introducing location-specific and time interval random effects which creates more parameters to estimate. Bayesian models implemented via Markov chain Monte Carlo simulation (MCMC) addresses fit of highly parameterized models.
This work applied zero-inflated Bayesian models to estimate malaria attributable mortality across all age-groups using large, correlated and sparse data collected from Navrongo and Manhiça HDSS between 2001 and 2004. The contributions of this thesis were (i) the description of the HDSS data characteristics and relevant methods for analysis; (ii) the spatially explicit estimates of malaria transmission intensity at monthly intervals; and (iii) the relationship between all-cause mortality and malaria transmission intensity across all age categories.
Chapter 2 described the characteristics of the MTIMBA data. These are large geostatistical, temporal, seasonal and zero-inflated data. The mortality and mosquito data were misaligned because they were captured at different compounds and time periods. Zero-inflated Bayesian spatio-temporal models are the state-of-art in handling such data. The rigorous statistical process was demonstrated by modelling sporozoite rate (SR) data from Manhiça HDSS. The analysis of the MTIMBA data was used as an avenue for building SSA capacity through course work, seminars and mentorship. Site-specific analyses are still on-going. However, the project generated data that is relevant for assessing within and between site malaria transmission heterogeneity.
The Navrongo malaria exposure surfaces described in chapter 3 were obtained from zero-inflated geostatistical models fitting separately the binomial SR data and negative binomial count data by mosquito species. All the models included space and time correlation in addition to the Climate, environmental and seasonality covariates. The entomological inoculation rate (EIR) estimates were derived as a product of predicted man biting rate and SR. Observed EIR in this district was >100 infective bites/person/year. Distance to water to bodies, day temperatures and vegetation were the main predictors of mosquito densities for the two species. The EIR maps clearly indicated that the temporal heterogeneity was stronger than the spatial variation in this area. The same situation was also observed from the analyses of the two MTIMBA sites of Rufiji (Tanzania) and Kisumu (Kenya).
Monthly malaria exposure surfaces (chapter 3) were linked to the nearest compounds where mortality was observed as described in chapter 4. Time to death data were split at monthly intervals in order to generate Bernoulli and binomial data that were modelled via logistic regression formulations. Spatio-temporal models were fitted to obtain age-specific mortality risk estimates. The model considered 2 covariates; natural logarithm transformed EIR estimates with their measurement errors and age. ITN variable was only included in neonates, post-neonates and child models. The analysis showed a positive log-linear relationship between all-cause mortality and malaria exposure in all the age groups but the association was only important among children (1-4 years) and people >= 60 years. ITN use showed a protective effect among all the under five children, confirming what was observed in Rufiji and Kisumu HDSS.
The methods used in estimating malaria exposure surfaces and mortality risks in chapters 3 and 4 were extended to Manhiça HDSS (Mozambique) data to describe the mortality-malaria transmission relationship for this area (chapter 5). The spatio-temporal age-specific models considered EIR estimates with their measurement errors (to account for the predictive uncertainty) and age as model covariates.
The distance to the nearest water bodies was the only important common predictor of An. funestus and An. gambiae mosquito densities. Malaria transmission intensity declined consistently in this area. The Model-based results indicated a positive log-linear relationship between all-cause mortality and malaria exposure across all age groups namely; the neonates (0-28 days), post-neonates (1-11months), children (1-4years), young people (5-14 years), adults (15- 59years) and old age (>=60 years).
This work contributes to further understand of malaria-mortality relationships. A positive association between mortality and malaria exposure among the under fives is consistent with what was reported from the MTIMBA sites of Rufiji and Kisumu. Completion of the remaining site-specific analyses followed by a meta-analysis will make a great contribution to malaria epidemiology. Further work however, should consider cohort analysis in order to ascertain whether malaria control interventions have caused a shift in the age of acquired immunity
Participatory mapping of target areas to enable operational larval source management to suppress malaria vector mosquitoes in Dar es Salaam, Tanzania.
No full textBACKGROUND\ud
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Half of the population of Africa will soon live in towns and cities where it can be protected from malaria by controlling aquatic stages of mosquitoes. Rigorous but affordable and scaleable methods for mapping and managing mosquito habitats are required to enable effective larval control in urban Africa.\ud
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METHODS\ud
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A simple community-based mapping procedure that requires no electronic devices in the field was developed to facilitate routine larval surveillance in Dar es Salaam, Tanzania. The mapping procedure included (1) community-based development of sketch maps and (2) verification of sketch maps through technical teams using laminated aerial photographs in the field which were later digitized and analysed using Geographical Information Systems (GIS).\ud
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RESULTS\ud
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Three urban wards of Dar es Salaam were comprehensively mapped, covering an area of 16.8 km2. Over thirty percent of this area were not included in preliminary community-based sketch mapping, mostly because they were areas that do not appear on local government residential lists. The use of aerial photographs and basic GIS allowed rapid identification and inclusion of these key areas, as well as more equal distribution of the workload of malaria control field staff.\ud
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CONCLUSION\ud
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The procedure developed enables complete coverage of targeted areas with larval control through comprehensive spatial coverage with community-derived sketch maps. The procedure is practical, affordable, and requires minimal technical skills. This approach can be readily integrated into malaria vector control programmes, scaled up to towns and cities all over Tanzania and adapted to urban settings elsewhere in Africa
Limited antigenic diversity of Plasmodium falciparumapical membrane antigen 1 supports the development of effective multi-allele vaccines
No full textBackground: Polymorphism in antigens is a common mechanism for immune evasion used by many important pathogens, and presents major challenges in vaccine development. In malaria, many key immune targets and vaccine candidates show substantial polymorphism. However, knowledge on antigenic diversity of key antigens, the impact of polymorphism on potential vaccine escape, and how sequence polymorphism relates to antigenic differences is very limited, yet crucial for vaccine development. Plasmodium falciparum apical membrane antigen 1 (AMA1) is an important target of naturally-acquired antibodies in malaria immunity and a leading vaccine candidate. However, AMA1 has extensive allelic diversity with more than 60 polymorphic amino acid residues and more than 200 haplotypes in a single population. Therefore, AMA1 serves as an excellent model to assess antigenic diversity in malaria vaccine antigens and the feasibility of multi-allele vaccine approaches. While most previous research has focused on sequence diversity and antibody responses in laboratory animals, little has been done on the cross-reactivity of human antibodies. Methods: We aimed to determine the extent of antigenic diversity of AMA1, defined by reactivity with human antibodies, and to aid the identification of specific alleles for potential inclusion in a multi-allele vaccine. We developed an approach using a multiple-antigen-competition enzyme-linked immunosorbent assay (ELISA) to examine cross-reactivity of naturally-acquired antibodies in Papua New Guinea and Kenya, and related this to differences in AMA1 sequence. Results: We found that adults had greater cross-reactivity of antibodies than children, although the patterns of cross-reactivity to alleles were the same. Patterns of antibody cross-reactivity were very similar between populations (Papua New Guinea and Kenya), and over time. Further, our results show that antigenic diversity of AMA1 alleles is surprisingly restricted, despite extensive sequence polymorphism. Our findings suggest that a combination of three different alleles, if selected appropriately, may be sufficient to cover the majority of antigenic diversity in polymorphic AMA1 antigens. Antigenic properties were not strongly related to existing haplotype groupings based on sequence analysis. Conclusions: Antigenic diversity of AMA1 is limited and a vaccine including a small number of alleles might be sufficient for coverage against naturally-circulating strains, supporting a multi-allele approach for developing polymorphic antigens as malaria vaccines
Modelling the seasonal and spatial variation of malaria transmission in relation to mortality in Africa
No full textAbout three billion people worldwide are estimated to be at risk of malaria transmission. In developing countries, malaria is believed to be a major cause of morbidity and mortality, mostly in children under five years. It is among the indirect causes of maternal mortality and infants’ deaths due to low-birth-weights. Malaria brings huge economic burden due to number of days lost during sickness and deaths, sustaining a vicious cycle of disease and poverty in sub Saharan Africa (SSA) and high attribute of disability-adjusted life years.
A number of malaria control interventions to reduce intensity of transmission have been successfully implemented in the regions of SSA, however, elimination of malaria is still a dream in many developing countries today. Failures in global eradication are related to resistance in insecticides and anti-malarial drugs, and health systems related factors. The Roll Back Malaria (RBM) partnership reinforced new strategies to combat malaria with long-term goal of eradicating the disease globally. This was facilitated by increasing funding for malaria research, improve multi disciplinary initiatives and make malaria among the main agenda of all international health and development forums. The reduction in mortality, especially in children has been reported recently and is associated with achievements in intervention strategies, improvements in malaria diagnosis and treatment. However, poor natural acquisition of malaria immunity in children as a consequence of weak or no exposure is a major epidemiological concern and brings a fear of higher mortality rates or shifting of age of death to older children. Understanding and quantify links between transmission, intervention, immunity and mortality is key for sustainable progress towards malaria control targets.
A comprehensive analysis of information on malaria transmission, vital events, drivers of transmission and mortality-related risk factors is required to achieve that. Lack of vital registration systems in developing countries hinders availability of appropriate data to conduct such analysis. Establishment of Demographic Surveillance Systems (DSS) in many developing countries aims to fill these information gaps. One of the initiatives integrated within DSSs is the Malaria Transmission Intensity and Mortality Burden across Africa (MTIMBA) project. The project compiled a database of mosquito collections at selected sites in Africa over a large number of locations, using standardized methodologies for a period of three years. The entomological parameters were linked with routinely monitored vital events within the DSS. The MTIMBA database is the most comprehensive entomological database ever collected in Africa which allows studying spatial-temporal variation in malaria transmission in relation to mortality.
Malaria is an environmental disease hence transmission varies with climate as it modifies population, survival, distribution and infectivity of malaria vectors. Quantification of association between climate and transmission is important to allow prediction of risk even in areas that field data cannot be easily obtained. Development in geographical information systems (GIS) and availability of remote sensing (RS) data facilitates availability of environment and climate data at high space and time resolutions allowing accurate estimation of outcome-factor relationship.
However, DSS data are large, sparse, zero-inflated and are characterized by seasonal patterns, spatial and temporal correlations. Standard models assume independence between observations, an assumption which do not hold for correlated data, hence utilizing these models might result into biased estimates. Geostatistical modeling of large, sparse and zero inflated space-time data is computational challenging specifically in the estimation of the spatial processes. The spatial correlation is accounted by introducing location-specific random effect parameters which are assumed to arise from a spatial process quantified by a multivariate normal distribution. The models are highly parameterized and their fit is computationally intensive. Bayesian computational algorithms such as Markov Chain Monte Carlo (MCMC) can be used to fit these models. Estimation of the spatial process requires inversion of the covariance matrix at each simulation point. The dimension of the matrix increases exponentially with number of locations and the inversion becomes infeasible when the size is too large. Recent techniques overcome this problem by approximating the spatial process from a subset of locations. These methods have been applied on Gaussian outcomes observed over a grid. Extension and formulation of rigorous methods to efficient model MTIMBA data are needed to allow precise prediction of malaria transmission at locations with mortality data to enhance studying the association. Lastly, seasonality in climatic conditions which introduces seasonal patterns in transmission and mortality data, should be accounted for when modelling such data.
The objectives of this thesis were to i) develop Bayesian geostatistical models to analyze very large and sparse geostatistical and temporal non-Gaussian data with seasonal patterns and ii) apply these models to (a) estimate space-time heterogeneity in malaria transmission (b) assess mortality variations between different ages during the first year of life while adjusting for seasonality and (c) determine the relation between transmission intensity and risk of mortality in children and adult population after taking into account control interventions. This work used an extract of MTIMBA data from the Rufiji DSS (RDSS) collected between October 2001 and September 2004.
Evaluation of approaches to capture seasonal pattern is discussed in Chapter 2 and applied to estimate mortality peaks at different stages of infant life. In Chapter 3, models approximating the spatial process from a subset of locations were developed to assess effect of climate, seasonal and spatial pattern of sporozoite rate (SR) of An. funestus and An. gambiae in RDSS. A rigorous approach to analyze malaria transmission data using Entomology Inoculation Rate (EIR) data, which is the product of mosquito density and SR, is discussed in Chapter 4. Zero-inflated models were used to account for over-dispersion and zero-inflation in the data. High resolution EIR estimates were produced for the RDSS. Exposure surfaces obtained in Chapter 4, were aligned with mortality events to assess the relationship between all-cause mortality and malaria transmission. Geostatistical Bernoulli discrete-time regression models adjusted for age and ITN possession were used for that analysis. The results of these analyses are presented in Chapters 5 and 6. The EIR was incorporated in the model as a covariate with measure of uncertainty.
This work is a building block on the insight and understanding of association between malaria transmission and all-cause mortality. The strength of results of this work relies on EIR estimates predicted at high spatial (household level) and temporal resolution by employing rigorous geostatistical models fitted on large entomological data. The better exposure estimates obtained are able to more accurately estimate the mortality-transmission relation
Endemic diseases and agricultural productivity: Challenges and policy response
No full textContrary to Asian countries, the agricultural sector in Africa had not benefited from the green revolution success. After a long time of disinterest in the agriculture sector in Africa, several voices arise now in favour of greater efforts towards this sector. Several studies tend to show the crucial role of agriculture in African countries’ growth and highlight the huge need of increasing the productivity in this sector. If increase in agriculture productivity requires both an expansion of irrigated areas and the adoption of high yield varieties, those innovations and their high development could be the source of negative health (and environmental) effects. Using a mega-analysis, this paper highlights first the links between health, disease and development and then agricultural productivity. The literature review shows that the negative effect of bad health was not systematically checked, and that the intensity of this effect depends of the disease, but also of the work productivity and the existence or not of a coping process. The second part of the paper focused on the development of high intensive agriculture as a risk factor for farmers’ and rural inhabitants’ health. This survey shows that whether irrigation and fertilizer and pest intensive use could be considered as highly health (and environmental) risk factors, appropriate control measures (such as for examples systematic maintenance of irrigation canals, alternate wetting and drying of irrigated fields or integrated pest management) considerably reduce this risk, while at the same time, increase the agriculture productivity.agriculture, productivity, endemic disease, health risk factor, Africa
Larval ecology of malaria vectors and the impact of larviciding on malaria transmission in The Gambia
No full textThe study reported in this thesis explored the ecology of aquatic stages of mosquitoes in the middle reaches of the Gambia River in order to assess the feasibility and impact of microbial larviciding on malaria transmission in large river ecosystems in sub- Saharan Africa. All accessible water bodies in four study zones covering 400 km(^2) were mapped and sampled for mosquitoes. Microbial larvicides were applied in the four zones in across-over design and the impact of larviciding on mosquito densities assessed. Anopheline and culicine mosquitoes were found in all sampled habitats, apart from those with moving water. Similarly, all habitats, except puddles and water channels, had similar larval and pupal densities. Anopheles gambiae sensu lato, the major malaria vector in Africa, exploited a wide range of habitats and despite a decrease in population density during the dry season, could be found in breeding sites throughout the year. Mosquitoes shared habitats with other invertebrates including their predators. A closer look at rice fields revealed that mosquitoes were abundant in rice fields closer to the landward edge of the floodplains where water is fresher and contains high quantifies of nutrients. Mosquitoes of The Gambia were highly susceptible to both Bacillus thuringiensis var. israelensis (Bti) and B. sphaericus microbials, however no residual activity against anopheline larvae was observed. The basic training of personnel in identification of habitats, calibration of application equipment and active larviciding proved to be successful. Routine larviciding was associated with > 91 % reducfion (p < 0.001) in anophelines late stage larval density and 72 % (p < 0.001) in culicines. Overall, larviciding was associated with a 28% (p = 0.005) reduction in the number of adult female Anopheles gambiae s.l. found indoors, although this rose to 42%, when the study zone with the greatest abundance of breeding sites was excluded from the analysis. No significant reduction in adult culicines was observed. Ground application of Bti in areas with extensive floodplains is unlikely to contribute to a substantial reduction in malaria transmission in The Gambia, therefore vector control in such areas should target adult mosquitoes
