Response to malaria epidemics in Africa.

Malaria epidemics affect nonimmune populations in many highland and semi-arid areas of Africa. Effective prevention of these epidemics is challenging, particularly in the highlands where predictive accuracy of indicators is not sufficiently high to allow decisions involving expensive measures such as indoor residual spraying of insecticides. Advances in geographic information systems have proved useful in stratification of areas to guide selective targeting of interventions, including barrier application of insecticides in transmission foci to prevent spread of infection. Because rainfall is associated with epidemics in semi-arid areas, early warning methods based on seasonal climate predictions have been proposed. For most areas, response measures should focus on early recognition of anomalies and rapid mass drug administration. Vector control measures are useful if abnormal transmission is highly likely and if they can be selectively implemented at the early stages of an outbreak

Early warning systems for malaria in Africa: from blueprint to practice.

Although the development of early warning systems for malaria has been advocated by international agencies and academic researchers for many years, practical progress in this area has been relatively modest. In two recent articles, Thomson et al. provide new evidence that models of malaria incidence that incorporate monitored or predicted climate can provide early warnings of epidemics one to five months in advance in semi-arid areas. Although the potential benefits of these models in terms of improved management of epidemics are clear, several technical and practical hurdles still need to be overcome before the models can be widely integrated into routine malaria-control strategies

Effect of environmental variables and kdr resistance genotype on survival probability and infection rates in Anopheles gambiae (s.s.).

BACKGROUND: Environmental factors, especially ambient temperature and relative humidity affect both mosquitoes and malaria parasites. The early part of sporogony is most sensitive and is affected by high temperatures and temperature fluctuation immediately following ingestion of an infectious blood meal. The aim of this study was to explore whether environmental variables such as temperature, together with the presence of the kdr insecticide resistance mutations, have an impact on survival probability and infection rates in wild Anopheles gambiae (s.s.) exposed and unexposed to a pyrethroid insecticide. METHODS: Anopheles gambiae (s.s.) were collected as larvae, reared to adults, and fed on blood samples from 42 Plasmodium falciparum-infected local patients at a health facility in mid-western Uganda, then exposed either to nets treated with sub-lethal doses of deltamethrin or to untreated nets. After seven days, surviving mosquitoes were dissected and their midguts examined for oocysts. Prevalence (proportion infected) and intensity of infection (number of oocysts per infected mosquito) were recorded for each group. Mosquito mortality was recorded daily. Temperature and humidity were recorded every 30 minutes throughout the experiments. RESULTS: Our findings indicate that apart from the effect of deltamethrin exposure, mean daily temperature during the incubation period, temperature range during the first 24 hours and on day 4 post-infectious feed had a highly significant effect on the risk of infection. Deltamethrin exposure still significantly impaired survival of kdr homozygous mosquitoes, while mean daily temperature and relative humidity during the incubation period independently affected mosquito mortality. Significant differences in survival of resistant genotypes were detected, with the lowest survival recorded in mosquitoes with heterozygote L1014S/L1014F genotype. CONCLUSIONS: This study confirmed that the early part of sporogony is most affected by temperature fluctuations, while environmental factors affect mosquito survival. The impact of insecticide resistance on malaria infection and vector survival needs to be assessed separately for mosquitoes with different resistance mechanisms to fully understand its implications for currently available vector control tools and malaria transmission

Exposure to deltamethrin affects development of Plasmodium falciparum inside wild pyrethroid resistant Anopheles gambiae s.s. mosquitoes in Uganda.

BACKGROUND: Pyrethroid resistance in African vector mosquitoes is a threat to malaria control. Resistant mosquitoes can survive insecticide doses that would normally be lethal. We studied effects of such doses on Plasmodium falciparum development inside kdr-resistant Anopheles gambiae s.s. in Uganda. METHODS: We collected An. gambiae s.s. homozygous for kdr-L1014S mutation, fed them on blood samples from 42 P. falciparum-infected local patients, then exposed them either to nets treated with sub-lethal doses of deltamethrin or to untreated nets. After seven days, we dissected 692 mosquitoes and examined their midguts for oocysts. Prevalence (proportion infected) and intensity of infection (number of oocysts per infected mosquito) were recorded for each group. RESULTS: Both prevalence and intensity of infection were significantly reduced in deltamethrin-exposed mosquitoes, compared to those exposed to untreated nets. With low doses (2.5-5.0 mg/m(2)), prevalence was reduced by 59% (95% CI = 22%-78%) and intensity by 41% (95% CI = 25%-54%). With high doses (10-16.7 mg/m(2)), prevalence was reduced by 80% (95% CI = 67%-88 %) and intensity by 34 % (95 % CI = 20%-46%). CONCLUSIONS: We showed that, with locally-sampled parasites and mosquitoes, doses of pyrethroids that are sub-lethal for resistant mosquitoes can interfere with parasite development inside mosquitoes. This mechanism could enable pyrethroid-treated nets to prevent malaria transmission despite increasing vector resistance

Forecasting malaria incidence from historical morbidity patterns in epidemic-prone areas of Ethiopia: a simple seasonal adjustment method performs best.

The aim of this study was to assess the accuracy of different methods of forecasting malaria incidence from historical morbidity patterns in areas with unstable transmission. We tested five methods using incidence data reported from health facilities in 20 areas in central and north-western Ethiopia. The accuracy of each method was determined by calculating errors resulting from the difference between observed incidence and corresponding forecasts obtained for prediction intervals of up to 12 months. Simple seasonal adjustment methods outperformed a statistically more advanced autoregressive integrated moving average method. In particular, a seasonal adjustment method that uses mean deviation of the last three observations from expected seasonal values consistently produced the best forecasts. Using 3 years' observation to generate forecasts with this method gave lower errors than shorter or longer periods. Incidence during the rainy months of June-August was the most predictable with this method. Forecasts for the normally dry months, particularly December-February, were less accurate. The study shows the limitations of forecasting incidence from historical morbidity patterns alone, and indicates the need for improved epidemic early warning by incorporating external predictors such as meteorological factors

Understanding the effects of dichotomization of continuous outcomes on geostatistical inference

Diagnosis is often based on the exceedance or not of continuous health indicators of a predefined cut-off value, so as to classify patients into positives and negatives for the disease under investigation. In this paper, we investigate the effects of dichotomization of spatially-referenced continuous outcome variables on geostatistical inference. Although this issue has been extensively studied in other fields, dichotomization is still a common practice in epidemiological studies. Furthermore, the effects of this practice in the context of prevalence mapping have not been fully understood. Here, we demonstrate how spatial correlation affects the loss of information due to dichotomization, how linear geostatistical models can be used to map disease prevalence and thus avoid dichotomization, and finally, how dichotomization affects our predictive inference on prevalence. To pursue these objectives, we develop a metric, based on the composite likelihood, which can be used to quantify the potential loss of information after dichotomization without requiring the fitting of Binomial geostatistical models. Through a simulation study and two applications on disease mapping in Africa, we show that, as thresholds used for dichotomization move further away from the mean of the underlying process, the performance of binomial geostatistical models deteriorates substantially. We also find that dichotomization can lead to the loss of fine scale features of disease prevalence and increased uncertainty in the parameter estimates, especially in the presence of a large noise to signal ratio. These findings strongly support the conclusions from previous studies that dichotomization should be always avoided whenever feasible

Travel and the emergence of high-level drug resistance in Plasmodium falciparum in southwest Uganda: results from a population-based study.

BACKGROUND: The I164L mutation on the dhfr gene confers high level resistance to sulfadoxine-pyrimethamine (SP) but it is rare in Africa except in a cluster of reports where prevalence >10% in highland areas of southwest Uganda and eastern Rwanda. The occurrence of the dhfr I164L mutation was investigated in community surveys in this area and examined the relationship to migration. METHODS: A cross-sectional prevalence survey was undertaken in among villages within the catchment areas of two health facilities in a highland site (Kabale) and a highland fringe site (Rukungiri) in 2007. Sociodemographic details, including recent migration, were collected for each person included in the study. A total of 206 Plasmodium falciparum positive subjects were detected by rapid diagnostic test; 203 in Rukungiri and 3 in Kabale. Bloodspot samples were taken and were screened for dhfr I164L. RESULTS: Sequence analysis confirmed the presence of the I164L mutations in twelve P. falciparum positive samples giving an estimated prevalence of 8.6% in Rukungiri. Of the three parasite positive samples in Kabale, none had I164L mutations. Among the twelve I164L positives three were male, ages ranged from 5 to 90 years of age. None of those with the I164L mutation had travelled in the 8 weeks prior to the survey, although three were from households from which at least one household member had travelled during that period. Haplotypes were determined in non-mixed infections and showed the dhfr I164L mutation occurs in both as a N51I + S108N + I164L haplotype (n = 2) and N51I + C59R + S108N + I164L haplotype (n = 5). Genotyping of flanking microsatellite markers showed that the I164L occurred independently on the triple mutant (N51I, C59R + S108N) and double mutant (N51I + S108N) background. CONCLUSIONS: There is sustained local transmission of parasites with the dhfr I164L mutation in Rukungiri and no evidence to indicate its occurrence is associated with recent travel to highly resistant neighbouring areas. The emergence of a regional cluster of I164L in SW Uganda and Rwanda indicates that transmission of I164L is facilitated by strong drug pressure in low transmission areas potentially catalysed in those areas by travel and the importation of parasites from relatively higher transmission settings

Application of Serological Tools and Spatial Analysis to Investigate Malaria Transmission Dynamics in Highland Areas of Southwest Uganda.

Serological markers, combined with spatial analysis, offer a comparatively more sensitive means by which to measure and detect foci of malaria transmission in highland areas than traditional malariometric indicators. Plasmodium falciparum parasite prevalence, seroprevalence, and seroconversion rate to P. falciparum merozoite surface protein-119 (MSP-119) were measured in a cross-sectional survey to determine differences in transmission between altitudinal strata. Clusters of P. falciparum parasite prevalence and high antibody responses to MSP-119 were detected and compared. Results show that P. falciparum prevalence and seroprevalence generally decreased with increasing altitude. However, transmission was heterogeneous with hotspots of prevalence and/or seroprevalence detected in both highland and highland fringe altitudes, including a serological hotspot at 2,200 m. Results demonstrate that seroprevalence can be used as an additional tool to identify hotspots of malaria transmission that might be difficult to detect using traditional cross-sectional parasite surveys or through vector studies. Our study findings identify ways in which malaria prevention and control can be more effectively targeted in highland or low transmission areas via serological measures. These tools will become increasingly important for countries with an elimination agenda and/or where malaria transmission is becoming patchy and focal, but receptivity to malaria transmission remains high

Variations in entomological indices in relation to weather patterns and malaria incidence in East African highlands: implications for epidemic prevention and control

<p>Abstract</p> <p>Background</p> <p>Malaria epidemics remain a significant public health issue in the East African highlands. The aim of this study was to monitor temporal variations in vector densities in relation to changes in meteorological factors and malaria incidence at four highland sites in Kenya and Uganda and to evaluate the implications of these relationships for epidemic prediction and control.</p> <p>Methods</p> <p>Mosquitoes were collected weekly over a period of 47 months while meteorological variables and morbidity data were monitored concurrently. Mixed-effects Poisson regression was used to study the temporal associations of meteorological variables to vector densities and of the latter to incidence rates of <it>Plasmodium falciparum</it>.</p> <p>Results</p> <p><it>Anopheles gambiae </it>s.s. was the predominant vector followed by <it>Anopheles arabiensis</it>. <it>Anopheles funestus </it>was also found in low densities. Vector densities remained low even during periods of malaria outbreaks. Average temperature in previous month and rainfall in previous two months had a quadratic and linear relationship with <it>An. gambiae </it>s.s. density, respectively. A significant statistical interaction was also observed between average temperature and rainfall in the previous month. Increases in densities of this vector in previous two months showed a linear relationship with increased malaria incidence.</p> <p>Conclusion</p> <p>Although epidemics in highlands often appear to follow abnormal weather patterns, interactions between meteorological, entomological and morbidity variables are complex and need to be modelled mathematically to better elucidate the system. This study showed that routine entomological surveillance is not feasible for epidemic monitoring or prediction in areas with low endemicity. However, information on unusual increases in temperature and rainfall should be used to initiate rapid vector surveys to assess transmission risk.</p

Costs of early detection systems for epidemic malaria in highland areas of Kenya and Uganda

BACKGROUND: Malaria epidemics cause substantial morbidity and mortality in highland areas of Africa. The costs of detecting and controlling these epidemics have not been explored adequately in the past. This study presents the costs of establishing and running an early detection system (EDS) for epidemic malaria in four districts in the highlands of Kenya and Uganda. METHODS: An economic costing was carried out from the health service provider's perspective in both countries. Staff time for data entry and processing, as well as supervising and coordinating EDS activities at district and national levels was recorded and associated opportunity costs estimated. A threshold analysis was carried out to determine the number of DALYs or deaths that would need to be averted in order for the EDS to be considered cost-effective. RESULTS: The total costs of the EDS per district per year ranged between US$ 14,439 and 15,512. Salaries were identified as major cost-drivers, although their relative contribution to overall costs varied by country. Costs of relaying surveillance data between facilities and district offices (typically by hand) were also substantial. Data from Uganda indicated that 4% or more of overall costs could potentially be saved by switching to data transfer via mobile phones. Based on commonly used thresholds, 96 DALYs in Uganda and 103 DALYs in Kenya would need to be averted annually in each district for the EDS to be considered cost-effective. CONCLUSION: Results from this analysis suggest that EDS are likely to be cost-effective. Further studies that include the costs and effects of the health systems' reaction prompted by EDS will need to be undertaken in order to obtain comprehensive cost-effectiveness estimates