1,721,162 research outputs found
Housing improvements and malaria risk in sub-Saharan Africa: a multi-country analysis of survey data
No full textBackground: Improvements to housing may contribute to malaria control and elimination by reducing house entry by malaria vectors and thus exposure to biting. We tested the hypothesis that the odds of malaria infection are lower in modern, improved housing compared to traditional housing in sub-Saharan Africa (SSA).Methods and Findings: We analysed 15 Demographic and Health Surveys (DHS) and 14 Malaria Indicator Surveys (MIS) conducted in 21 countries in SSA between 2008 and 2015 that measured malaria infection by microscopy or rapid diagnostic test (RDT). DHS/MIS surveys record whether houses are built with finished materials (e.g., metal) or rudimentary materials (e.g., thatch). This information was used to develop a binary housing quality variable where houses built using finished wall, roof, and floor materials were classified as “modern”, and all other houses were classified as “traditional”. Conditional logistic regression was used to determine the association between housing quality and prevalence of malaria infection in children aged 0–5 y, adjusting for age, gender, insecticide-treated net (ITN) use, indoor residual spraying, household wealth, and geographic cluster. Individual survey odds ratios (ORs) were combined to determine a summary OR using a random effects meta-analysis. Of 284,532 total children surveyed, 139,318 were tested for malaria infection using microscopy (n = 131,652) or RDT (n = 138,540). Within individual surveys, malaria prevalence measured by microscopy ranged from 0.4% (Madagascar 2011) to 45.5% (Burkina Faso 2010) among children living in modern houses and from 0.4% (The Gambia 2013) to 70.6% (Burkina Faso 2010) in traditional houses, and malaria prevalence measured by RDT ranged from 0.3% (Senegal 2013–2014) to 61.2% (Burkina Faso 2010) in modern housesand from 1.5% (The Gambia 2013) to 79.8% (Burkina Faso 2010) in traditional houses. Across all surveys, modern housing was associated with a 9% to 14% reduction in the odds of malaria infection (microscopy: adjusted OR 0.91, 95% CI 0.85–0.97, p = 0.003; RDT: adjusted OR 0.86, 95% CI 0.80–0.92, p<0.001). This association was consistent regardless of ITN usage. As a comparison, the odds of malaria infection were 15% to 16% lower among ITN users versus non-users (microscopy: adjusted OR 0.84, 95% CI 0.79–0.90, p<0.001; RDT: adjusted OR 0.85, 95% CI 0.80–0.90, p<0.001). The main limitation of this study is that residual confounding by household wealth of the observed association between housing quality and malaria prevalence is possible, since the wealth index may not have fully captured differences in socioeconomic position; however, the use of multiple national surveys offers the advantage of a large sample size and the elimination of many biases typically associated with pooling observational data.Conclusions: Housing quality is an important risk factor for malaria infection across the spectrum of malaria endemicity in SSA, with a strength of association between housing quality and malaria similar to that observed between ITN use and malaria. Improved housing should be considered a promising intervention for malaria control and elimination and long-term prevention of reintroduction.</p
Malaria epidemiology and key control interventions in the Democratic Republic of Congo
Full text linkMalaria remains a major global public health problem causing over 400,000 deaths annually, mainly among children in sub Saharan Africa. The Democratic Republic of Congo (DRC), the second largest and the fourth most populated country in Africa, is one of the most malarious countries in the world. An estimated 97% of its 71 million inhabitants live in high transmission areas. Together with Nigeria, DRC accounts for about 40% of the total estimated malaria cases worldwide, and for more than 35% of the total estimated malaria deaths. The national malaria control programme (NMCP) is committed to reducing malaria and the associated morbidity and mortality in DRC through the implementation of specific proven interventions. The aim of this thesis was to contribute to the improvement of malaria control activities in the DRC, through the provision of new evidence on the epidemiology of malaria and key control interventions, to support evidence-based policy making.
Kinshasa, the capital of DRC, has been expanding very rapidly in the past 20 years (going from an estimated 3 million inhabitants to a current estimate of 10 million) and available evidence has shown that urbanization had a significant impact on the ecosystems and disease patterns, including malaria. However, in the context of scaling up of interventions, data on malaria distribution in Kinshasa are scarce; the latest epidemiological study was conducted in 2000. We conducted two cross-sectional surveys to update malaria risk stratification in Kinshasa, identify factors contributing to the distribution patterns, and update information on malaria control activities. Geo-referenced data for key parameters were mapped at the level of the health area (HA) by means of a geographic information system (GIS). The overall standardized malaria prevalence was 11.7%, showing a decline compared to previous studies. The spatial distribution showed higher malaria risk in the peri-urban areas compared to the more urban central areas. Compared to the Demographic and Health Survey 2007 (DHS-DRC, 2007), coverage of malaria control measures showed considerable progresses in a pattern inversely proportional to the malaria risk distribution: low LLIN coverage in the peri-urban areas and higher coverage in the centre of the city. The analysis of drivers of malaria in both children less than five years and individuals aged older than five years highlighted the variation of the effect of age and reported history of fever by level of endemicity. In low endemicity strata, a shift in the peak of malaria prevalence towards the older age groups was observed, while the history of fever in the last two weeks increased the risk of malaria in all age groups and regardless of the level of endemicity. Individual use of LLIN was associated with reduced risk malaria infection among children less than five years. The risk of malaria was lower among children less than five years of the wealthiest socio economic group. This risk map constitutes a strong basis for the planning of malaria control interventions in Kinshasa.
Following the publication of the results of two large open-label randomized controlled trials (SEAQUAMAT, AQUAMAT) that demonstrated the benefits of injectable artesunate over quinine in the treatment of severe malaria, and in line with the updated WHO guidelines, the NMCP changed the policy for treating severe malaria in children and adults from injectable quinine to injectable artesunate in 2012 A transition period of 3 years was set, including the need for operational research to support the national deployment. We conducted an operational comparative study of quinine and injectable artesunate for the treatment of severe malaria (MATIAS study) with the aims of assessing the operational feasibility of this introduction, providing national cost estimates, and assessing the acceptability of the new drug among both health care providers and patients. Our findings showed that all the operational parameters measured (time to discharge, interval between admission and the start of intravenous treatment, personnel time spent on patient management, and parasite clearance time) were equal or in favour of injectable artesunate. The mean total cost per patient treated for severe malaria in hospitals and health centres was also lower with injectable artesunate. There was a high acceptability by both health care providers and patients. These findings support the rapid scale up of injectable artesunate in the country.
Mass distribution campaigns of LLIN are accepted as the best approach to rapidly increase coverage and use. To promote correct and consistent use of distributed LLIN, the WHO recommends the integration of door-to-door visits with “hang up” activities into mass distribution campaigns. Integrating hang-up activities requires obviously additional human and financial resources. Since published data on the effects and cost of door-to-door visits with hang up activities on LLIN use are scarce, more evidence is still required to optimize the efficiency of national LLIN programmes. We used a LLIN mass distribution campaign in the province of Kasai Occidental that used two different approaches, a fixed delivery strategy and a door-to-door strategy including hang-up activities, to evaluate comparatively household LLIN ownership, access and individual use, and examine factors associated with LLIN use. We also compared the two delivery strategies with regard to the LLIN coverage achieved and the cost of implementation. Results showed that the mass distribution campaign was effective at achieving high LLIN ownership and use. Having sufficient numbers of LLIN to cover all residents in the household was the strongest determinant of LLIN use. Compared with the door-to-door strategy, the fixed delivery strategy achieved a higher LLIN coverage at lower delivery cost, and seems to be a better LLIN delivery option in the context of DRC.
Information on the number and distribution of malaria cases and deaths is fundamental for the design, implementation and evaluation of malaria control programmes. In many endemic areas, health facility-based data remain the only consistent and readily available source of information on malaria. Because of known inherent limitations, this source of date can underestimate the total burden of disease by a considerable fraction. In DRC, the use of rapid diagnostic tests has been expanded since 2010, leading to a marked increase in suspected malaria cases receiving a diagnostic test. Together with other management measures, this should improve the quality of the incidence rates obtained through the Health Monitoring Information System (HMIS). Based on household survey data, the Malaria Atlas Project (MAP) of the University of Oxford has produced estimates of clinical incidence of malaria for the years 2000-2015 for all African countries, providing something like a reference value on incidence rates. We compared the malaria incidence rates obtained from the HMIS data in the DRC from 2010 to 2014 to the MAP modelled incidence rates for the same time period, in order to assess the relative reporting of the HMIS system. Our preliminary results showed that due to the expansion of parasitological diagnosis, the number of confirmed malaria cases reported and hence the fraction of incident cases captured by the HMIS data had increased substantially over time. By contrast, the number of incident malaria cases predicted by the MAP model had progressively decreased. Because of inconsistencies in reporting, it has been difficult to establish trends in malaria morbidity, but the unchanged high values of test positivity rates suggest malaria transmission remains high and stable over time
Application of mathematical modeling for malaria control decision-making in settings of varying transmission intensity
Full text linkPlanning for the control of Plasmodium falciparum malaria at the population level demands models of malaria epidemiology that provide realistic quantitative prediction of likely epidemiological outcomes of a wide range of control strategies. This project applies mathematical modeling parameterized both generally and with site-specific field data to better understand transmission dynamics of malaria across sites with varying transmission intensity and seasonality, primarily the highlands of western Kenya and in the lowlands of Zambia's Southern Province. Simulation results explore possible epidemiological scenarios for malaria in the presence and absence of a mix of control interventions, and for different amounts and patterns of seasonality of transmission. Together with a cost effectiveness analysis, results form the basis of recommendations for control programs. Individual-based stochastic models of malaria epidemiology were developed by the Swiss Tropical and Public Health Institute (Swiss TPH). To provide the site-specific parameters needed to fit the models to the study areas data on existing entomological, demographic, intervention deployment and health systems was gathered from field studies conducted by collaborating institutes and a literature review. Model simulations were run on an ensemble of models with multiple random seeds on the OpenMalaria simulator. Simulation outputs were compared to the observed data from the study areas in order to assess the validity of the model and a sensitivity analysis was conducted to address uncertainty. The model was then used to predict the impact of different combinations of malaria control interventions, and the impact of different seasonal transmission patterns, on impact measures. The models were able to simulate the transmission patterns of malaria in the study areas of western Kenyan highlands and Zambia lowlands and gain insight into the potential impact of malaria control interventions currently being un- or under- utilized in these areas. Despite the ability of mathematical modeling to be used to translate between measures of malaria transmission and indicators of disease burden in areas where sparse data renders evidence-based programmatic decision-making challenging, these models remain largely inaccessible to program managers. Results from such models can provide public health officials with accurate estimates of transmission, by seasonal pattern, that are necessary for assessing and tailoring malaria control and elimination programs to specific settings
Towards malaria prediction in Sri Lanka. modelling spatial and temporal variability of malaria case counts
Full text linkThis thesis was motivated by the need of the Anti Malaria Campaign (AMC) of Sri
Lanka for malaria risk maps and malaria case number predictions to assist in the
planning for malaria control. Despite a wealth of high resolution data collected over
decades, a malaria forecasting system was not in place, and detailed island-wide maps
of malaria incidence could permit the assessment of the malaria situation and its
determinants. The overall aim of this thesis was to describe the spatial and seasonal
distribution of malaria in Sri Lanka and associated factors, and to develop a malaria
forecasting system.
In this thesis, the spatial variation of malaria in Sri Lanka was described in relation to
risk factors. Also, the risk and the impact of a tsunami natural disaster on malaria
transmission and malaria control in Sri Lanka were evaluated. The relation in space
between seasonality of malaria and seasonality of rainfall, and the relationship
between monthly malaria case time series and monthly rainfall time series in Sri
Lanka were quantified. A model for short term malaria prediction was developed and
implemented in Sri Lanka for use by the AMC. This thesis also contributed a
statistical methodology for analysing over dispersed temporal count data with non
stationary and / or seasonal behaviour, such as observed in malaria case count time
series in Sri Lanka.
In Chapter 1, the stage was set by briefly describing malarial disease and the biology
of malarial parasites and vectors relevant to Sri Lanka. The influence of weather on
malaria transmission, and observed linkages between weather and malaria in terms of
spatial and temporal patterns were introduced. Immunity was also briefly discussed,
because it affects the translation of (unobserved) disease transmission patterns into
patterns of observed malaria cases. A brief overview was given of the history of
malaria and malaria control in Sri Lanka.
Chapter 2 provided health professionals and the larger general public with the first
island-wide incidence maps of Plasmodium vivax and Plasmodium falciparum
malaria at sub district resolution. The distribution and seasonality of P. vivax and P.
falciparum incidence was remarkably similar within each district, although they
varied spatially. The annual malaria incidence changed over the 1995 – 2002 period,
and the rate of change varied with the area, thus indicating the need for regular updates of the incidence maps. The spatial and temporal malaria distribution in the
country was related to accessibility of areas for implementation of malaria control (in
particular governed by the armed conflict and the peace process), and to socio
economic and environmental factors. Also, the exposure of tourists to malaria
infection was discussed.
Chapter 3 provided a re-assessment of the malaria situation, including details on
vector insecticide resistance, parasite drug resistance, and insights into the national
policy for malaria diagnosis and treatment. The assessment and its publication were
triggered by the tsunami that hit on 26 December 2004, and the ensuing international
concern about possibilities of an increase of vector borne diseases. The likelihood of
a widespread outbreak was estimated as limited. The public health system was
deemed capable of dealing with the possible threat of a malaria outbreak. Concerns
were expressed that the influx of foreign medical assistance, drugs, and insecticides
could interfere with malaria surveillance, and the long term malaria control strategy of
Sri Lanka, if not in accordance with government policy.
Chapter 4 assessed the impact of the tsunami on the malaria situation and the national
and international malaria control efforts in the year following the tsunami. Malaria
incidence had decreased in most districts, including the ones that were hit hardest by
the tsunami, and the whole-country malaria incidence time series did not deviate from
the downward trend that started in 2000. The focus of national and international post
tsunami malaria control efforts was supply of antimalarials, distribution of
impregnated mosquito nets and increased monitoring in the affected area.
Internationally donated antimalarials were either redundant or did not comply with
national drug policy. There was no indication of increased malaria vector density.
In Chapter 5, the spatial correlation between average seasonality of malaria and climatic seasonality of rainfall was studied. A simple index for seasonality was
developed by making use of the characteristic of a varying degree of bimodality of
seasonality present in both malaria and rainfall in Sri Lanka. The malaria seasonality
index was significantly associated with the rainfall seasonality index in a regression
taking spatial autocorrelation into account. This was in paradox with the negative
correlation in space between annual rainfall and malaria endemicity (Chapter 2). Both
rainfall and malaria may react independently to monsoonal periodicity, but given the
fact that rainfall has an important impact on the availability and quality of breeding sites for malaria vectors, it is clear that rainfall seasonality is an important driver of
malaria seasonality.
In Chapter 6, the temporal correlation between monthly malaria case time series and
monthly rainfall time series was explored for each district separately. For most
districts, strong positive correlations were found for malaria time series lagging zero
to three months behind rainfall. However, only for a few districts, weak positive (at
lags zero and one) or weak negative (at lags two to six) correlations were found if
autocorrelation and seasonality were removed from the series prior to crosscorrelation
analysis, thus indicating that rainfall might have little potential use in a
malaria forecasting system. These cross correlation analyses had the drawbacks that
inter-annual effects were masked due to detrending of the data, and that potentially
seasonally varying effects were not taken into account. Subsequent inter-annual
analysis showed strong negative correlations between malaria and rainfall for a group
of districts in the centre-west of the country. Seasonal inter-annual analysis showed
that the effect of rainfall on malaria varied according to the season (and geography).
Chapter 7 focused on the development of a malaria forecasting system for Sri Lanka,
which could assist in the efficient allocation of resources for malaria control,
especially when malaria is unstable and fluctuates in intensity both spatially and
temporally. Several types of time series models were tested in their ability to predict
the monthly number of malaria cases in districts one to four months ahead. Different districts required different prediction models, and the prediction accuracy varied with
district and forecasting horizon. It was subsequently tested if rainfall or malaria
patterns in neighbouring districts could improve prediction accuracy of the selected
models. Only for a few districts, a modest improvement was made when rainfall was
included in the models as a covariate. This modest improvement was not deemed
sufficient to merit investing in a forecasting system for which rainfall data are
routinely processed. The development and launch of a system for forecasting malaria
by the AMC was described in addendum to Chapter 7.
Throughout the statistical modelling in Chapter 7, it was assumed that logarithmically
transformed malaria case data were approximately Gaussian distributed. However,
such an approximation is less close when case numbers are low, as was the case at the
time of writing. Therefore, in Chapter 8, a class of generalised multiplicative seasonal
autoregressive integrated moving average models for the parsimonious and observation-driven modelling of non Gaussian, non stationary and / or seasonal time
series data was developed.
Chapter 9 provides a general discussion in which the contributions of this thesis are
put into context, in which limitations of this thesis are discussed and directions for
future research outlined
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Spatial statistical analysis, modelling and mapping of malaria in Africa
Full text linkEstimates of the disease burden due to malaria in Africa show that the toll it is
exacting in terms of loss of life, episodes of serious illness, and impediment to
economic development is enormous. In many areas the situation has become worse
due to failing drugs, failing insecticides, failing health systems, large scale population
movements and possibly due to co-infection with HIV. On the other hand, recent
studies have shown that widespread use of insecticide treated bed nets has the
potential for making substantial inroads into this disease burden, particularly in areas
of high endemicity. Recording the geographical distribution of any major disease forms an important basis
for locating appropriate interventions for its control and a means to monitoring their
effectiveness. It also provides a possibility for identifying ecological factors with
which the disease may be associated. The objective of this thesis was to produce evidence-based maps of malaria
prevalence and incidence by means of spatial statistical modelling; to evaluate and
advance the application of methodology in the analysis of spatially correlated disease
data; and to undertake detailed analysis of malaria incidence for one particular area in
order to establish underlying patterns of malaria risk over space and time and in
relation to population, climatic and environmental factors. Altogether six individual
studies were carried out, which modelled malaria distribution at three different levels
of scale. These levels and their locations, were: regional level in sub-Saharan West
Africa, country level in Mali and district level in Ubombo and Ngwavuma in
KwaZulu Natal, South Africa. In the case of the regional and country maps, the
malariometric measure was parasite prevalence in children, obtained from the MARA
database. In the case of the district-level analysis, routinely recorded small area
malaria incidence data were used, which were obtained from the provincial malaria
control programme. Three of the studies modelled malaria distribution over space and
time. There are well-documented difficulties with the mapping of raw disease rates, since
such maps will be dominated by sampling variability and analyses based on them will
be flawed due to the lack of independence in the rates. Spatial statistical methods can
be used to overcome these difficulties, but these have rarely been applied in the
context of malaria distribution modelling. In this thesis two such approaches were
employed: 1) classical geo-statistical methods, based on variograms and generalised
linear mixed models, and 2) autoregressive models in a Bayesian context using
Markov Chain Monte Carlo (MCMC) methods. Some minor adaptations of the
methods have been suggested. The main findings of the studies carried out in this thesis were: Both classical geostatistical and autoregressive MCMC methods are feasible
for modelling malaria distribution and advantages and limitations of each
method have to be weighed up in a particular context. The development of
extensions to the MCMC spatial modelling approach to cater for point
referenced (as opposed to areal) spatial data will make this method more
generally applicable. The ability to adequately reflect the effects of random
errors comprehensively in the resulting map estimates is an important
advantage of the Bayesian modelling approach. It is feasible to produce evidence-based maps of transmission intensity, which
are a refinement of expert opinion maps, from parasite ratio surveys. Malariometric measures of transmission intensity (and their proxies) are often
highly correlated in space as well as in time and this must be taken into
account in any modelling, particularly at the short range scales. Due to strong spatial heterogeneity it is difficult to model malaria transmission
intensity without leaving considerable unexplained, residual variation, which
may be spatially correlated. It is therefore unsatisfactory to map model
predictions directly. One method of overcoming this problem is to produce a
map of kriged (interpolated) model residuals, and to add these to model
predictions which can then be mapped. In large heterogeneous regions, models
should be derived within ecological zones, and special smoothing methods should be employed in boundary areas between these zones, rather than
attempting to derive a single unified distribution model for the whole region. Spatial variation in malaria transmission intensity is significantly associated
with basic climatic factors in areas of endemic stable malaria and in areas of
epidemic unstable malaria, but the relationship is usually not straightforward.
However, an association between temporal variation in malaria transmission
intensity and variation in weather, whilst plausible, could not be proven in the
data that were analysed. Sharp increases in malaria caseloads in Kwa Zulu Natal appear to originate
mainly from areas of previously low incidence, whilst high incidence areas
have partly stabilized. This suggests a geographical expansion of malarious
areas, and the acquisition of clinical tolerance to disease in some individuals in
high incidence areas. The finding that adults in high transmission sub-regions
of the province experience lower incidence rates than teenagers, supports the
hypothesis of clinical immunity to infection in these relatively high incidence
areas. Children under five in the same area, experience the lowest incidence
rates compared to other age groups, possibly as a result of being more
adequately protected by vector control measures than older children and
adults. In areas of unstable fluctuating malaria transmission intensity, incidence in
individual localities is highly correlated to incidence at the same locality in
previous seasons. One of the maps (West Africa) that were produced in this thesis has already been put
to use in malaria control. The findings relating to Kwa Zulu Natal will be presented
directly to the provincial malaria control programme. Two of the six studies have
been published, three have been submitted for publication and one is being prepared
for submission, to ensure widespread dissemination of the findings. A number of future research questions arise out of this work. These are, amongst
others: Methodological development of Bayesian spatial modelling software,
particularly to accommodate point referenced spatial data. Further analysis using the MARA database to produce endemicity maps of
other regions in Africa. Prospective studies should be undertaken to assess the relationship between
malaria and weather changes in epidemic prone areas, with a view to further
exploring the feasibility of epidemic forecasting systems. Further investigation of factors that influence the acquisition of clinical
immunity in adults in areas of moderate transmission intensity; investigation
whether this is confirmed in similar areas elsewhere (e.g. Namibia, Botswana),
and whether it is supported by age specific differences in case-fatality rates
South African Tuberculosis mortality data - showing the first sign of the AIDS epidemic?
No full textNo Abstract
The combined use of Indoor Residual Spraying and Long-Lasting Insecticidal Nets for malaria reduction in endemic rural Tanzania:\ud A cross sectional entomological survey dataset
Full text linkResearch outputs produced through repeated cross sectional entomological surveys in rural Tanzania for the purpose of evaluating the compbined impact of Long-Lasting Insecticidal Nets (LLIN) and Indoor Residual Spraying on malaria transmission, in comparison to sole use of LLIN. Information collected includes: total mosquitoes collected inside the household, details of house structure (type of wall and roof, presence of open eaves, ceiling and window screens), presence of livestock, whether the house was sprayed, as well as bed net ownership and usage. Information on Anopheles species and sporozoite rates is also provided
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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