The development of Malaria Early Warning Systems for Africa

Current efforts to predict malaria epidemics focus on the role weather anomalies can play in epidemic prediction. Alongside weather monitoring and seasonal climate forecasts, epidemiological, social and environmental factors can also play a role in predicting the timing and severity of malaria epidemics. Such factors can be incorporated into a framework for malaria early warning.     

Understanding and improving access to prompt and effective malaria treatment and care in rural Tanzania: the ACCESS Programme

Background

Malaria is a significant public health problem in Tanzania. Approximately 16 million malaria cases are reported every year and 100,000 to 125,000 deaths occur. Although most of Tanzania is endemic to malaria, epidemics occur in the highlands, notably in Kagera, a region that was subject to widespread malaria epidemics in 1997 and 1998. This study examined the relationship between climate and malaria incidence in Kagera with the aim of determining whether seasonal forecasts may assist in predicting malaria epidemics.

Methods

A regression analysis was performed on retrospective malaria and climatic data during each of the two annual malaria seasons to determine the climatic factors influencing malaria incidence. The ability of the DEMETER seasonal forecasting system in predicting the climatic anomalies associated with malaria epidemics was then assessed for each malaria season.

Results

It was found that malaria incidence is positively correlated with rainfall during the first season (Oct-Mar) (R-squared = 0.73, p < 0.01). For the second season (Apr-Sep), high malaria incidence was associated with increased rainfall, but also with high maximum temperature during the first rainy season (multiple R-squared = 0.79, p < 0.01). The robustness of these statistical models was tested by excluding the two epidemic years from the regression analysis. DEMETER would have been unable to predict the heavy El Niño rains associated with the 1998 epidemic. Nevertheless, this epidemic could still have been predicted using the temperature forecasts alone. The 1997 epidemic could have been predicted from observed temperatures in the preceding season, but the consideration of the rainfall forecasts would have improved the temperature-only forecasts over the remaining years.

Conclusion

These results demonstrate the potential of a seasonal forecasting system in the development of a malaria early warning system in Kagera region.     

The uncertain burden of Plasmodium falciparum epidemics in Africa

Although the control of malaria epidemics has been a priority for the World Health Organization and other agencies for many years, surprisingly little is known about the public health burden of these epidemics. Here, we evaluate the available evidence of the morbidity and mortality impacts of individual epidemics in Africa and examine the problems associated with using these data to estimate the average annual burden of epidemics at national and continental scales. We argue that conventional approaches that are used to assess the burden of epidemics are inadequate, and outline the future steps that are required to produce estimates that are more accurate.     

Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing.     

Control of epidemic malaria on the highlands of Madagascar

The Malagashy national malaria control programme ('Programme National de Lutte contre le Paludisme', PNLP) has been developing, since 1996, an epidemiological early warning system for malaria epidemics in the Central Highlands with the support of the Italian Development Cooperation. The system is based on the monitoring of malaria morbidity (clinical diagnosis) in 536 peripheral health centres (CSB) of the Highlands. The intervention area corresponds to 27 districts of the Antananarivo and Fianarantsoa provinces (4.7 million inhabitants) and spans around 100,000 square km. For each CSB a monthly warning threshold, defined as the 1993-1996 monthly mean number of malaria cases plus two standard deviations, was established. Three levels of epidemic alert have been defined according to the number of times the cases of presumptive malaria surpassed the threshold and according to the reported presence of severe malaria cases. The surveillance system relies also on the monitoring, in district hospitals of the Highlands, of the Plasmodium falciparum infection rate among clinically diagnosed malaria cases. A total of 185,589 presumptive malaria cases, corresponding to a 42/1000 malaria incidence, were recorded in 1997 by the surveillance system. During the same year 184 alerts of 2nd degree were reported. During 1998 173,632 presumptive malaria cases corresponding to a 38/1000 incidence were reported and 207 alerts of 2nd degree were detected; 75 of these alerts were investigated with ad hoc surveys and 3 initial malaria epidemics identified and controlled. Out of 6884 presumptive malaria cases diagnosed in the district hospitals during 1997-1998, only 835 (12.1%) have been confirmed by microscopy (P. falciparum 81.7%, P. vivax 15.0%, P. malariae 2.5%, P. ovale 0.2%, mixed infections 0.6%); 22.4% of these infections were imported cases from coastal endemic areas. The efficiency of the system in monitoring the trend of malaria morbidity and in the rapid detection and response to malaria epidemics is still being evaluated.     

Malaria early warning in Kenya

Kenya displays large spatiotemporal diversity in its climate and ecology. It follows that malaria transmission will reflect this environmental heterogeneity in both space and time. In this article, we discuss how such heterogeneity, and its epidemiological consequences, should be considered in the development of early warning systems for malaria epidemics.     

Coalescent inference for infectious disease: meta-analysis of hepatitis C

Genetic analysis of pathogen genomes is a powerful approach to investigating the population dynamics and epidemic history of infectious diseases. However, the theoretical underpinnings of the most widely used, coalescent methods have been questioned, casting doubt on their interpretation. The aim of this study is to develop robust population genetic inference for compartmental models in epidemiology. Using a general approach based on the theory of metapopulations, we derive coalescent models under susceptible–infectious (SI), susceptible–infectious–susceptible (SIS) and susceptible–infectious–recovered (SIR) dynamics. We show that exponential and logistic growth models are equivalent to SI and SIS models, respectively, when co-infection is negligible. Implementing SI, SIS and SIR models in BEAST, we conduct a meta-analysis of hepatitis C epidemics, and show that we can directly estimate the basic reproductive number (R₀) and prevalence under SIR dynamics. We find that differences in genetic diversity between epidemics can be explained by differences in underlying epidemiology (age of the epidemic and local population density) and viral subtype. Model comparison reveals SIR dynamics in three globally restricted epidemics, but most are better fit by the simpler SI dynamics. In summary, metapopulation models provide a general and practical framework for integrating epidemiology and population genetics for the purposes of joint inference.     

Regulation of immunity to Plasmodium: Implications from mouse models for blood stage malaria vaccine design

Malaria, a disease caused by the protozoan parasite Plasmodium, remains a serious healthcare problem in developing countries worldwide. While the host-parasite relationship in humans has been difficult to determine, the pliability of murine malaria models has enabled valuable contributions to the understanding of the pathogenesis of disease. Although no single model reflects precisely malaria infection of the human, different models collectively provide important information on the mechanisms of protective immunity and immunopathogenesis. This review summarizes progress towards understanding the broad spectrum of immune responsiveness to the blood stages of the malaria parasite during experimental infections in mice and highlights how examination of murine malarias sheds light on the factors involved in the modulation of vaccine-potentiated immunity.     

The first Finnish malariologist, Johan Haartman, and the discussion about malaria in 18th century Turku, Finland

After the Great Northern War in 1721, Sweden ceased to be an important military power. Instead, the kingdom concentrated on developing science. Swedish research got international fame with names as Carolus Linnaeus, Pehr Wargentin and Anders Celsius. Medical research remained limited and malaria was common especially in the coastal area and along the shores of the big lakes.Already in the beginning of the 18th century Swedish physicians recommended Peruvian bark as medication and they also emphasized that bleeding or blood-letting a malaria patient was harmful. Although malaria was a common disease in the kingdom, the situation was worst in the SW-part of Finland which consisted of the town of Turku and a large archipelago in the Baltic. The farmers had no opportunity to get modern healthcare until Johan Haartman was appointed district physician in 1754. To improve the situation he wrote a medical handbook intended for both the farmers and for persons of rank. Haartman's work was first published 1759 and he discussed all the different cures and medications. His aim was to recommend the best ones and warn against the harmful. His first choice was Peruvian bark, but he knew that the farmers could not afford it. Haartman was appointed professor in medicine at the Royal Academy of Turku in 1765. The malaria situation in Finland grew worse in the 1770's and Haartman analysed the situation. He found the connection between the warm summers and the spring epidemics next year.In a later thesis, Haartman analysed the late summer/early autumn malaria epidemics in the archipelago. Althouh Haartman did not know the connection between malaria and the vector, he gave astute advice and encouraged the farmers to build their cottages in windy places away from the shallow bays in which the Anopheles females hatched. Haartman died in 1788. After his death malaria research in Turku declined. His medical handbook would not be replaced until 1844.     

The El Niño southern oscillation and malaria epidemics in South America

A better understanding of the relationship between the El Ni?o Southern Oscillation (ENSO), the climatic anomalies it engenders, and malaria epidemics could help mitigate the world-wide increase in incidence of this mosquito-transmitted disease. The purpose of this paper is to assess the possibility of using ENSO forecasts for improving malaria control. This paper analyses the relationship between ENSO events and malaria epidemics in a number of South American countries (Colombia, Ecuador, French Guiana, Guyana, Peru, Suriname, and Venezuela). A statistically significant relationship was found between El Ni?o and malaria epidemics in Colombia, Guyana, Peru, and Venezuela. We demonstrate that flooding engenders malaria epidemics in the dry coastal region of northern Peru, while droughts favor the development of epidemics in Colombia and Guyana, and epidemics lag a drought by 1 year in Venezuela. In Brazil, French Guiana, and Ecuador, where we did not detect an ENSO/malaria signal, non-climatic factors such as insecticide sprayings, variation in availability of anti-malaria drugs, and population migration are likely to play a stronger role in malaria epidemics than ENSO-generated climatic anomalies. In some South American countries, El Ni?o forecasts show strong potential for informing public health efforts to control malaria.     

Regime shifts and heterogeneous trends in malaria time series from Western Kenya Highlands

Large malaria epidemics in the East African highlands during the mid and late 1990s kindled a stream of research on the role that global warming might have on malaria transmission. Most of the inferences using temporal information have been derived from a malaria incidence time series from Kericho. Here, we report a detailed analysis of 5 monthly time series, between 15 and 41 years long, from West Kenya encompassing an altitudinal gradient along Lake Victoria basin. We found decreasing, but heterogeneous, malaria trends since the late 1980s at low altitudes (<1600 m), and the early 2000s at high altitudes (>1600 m). Regime shifts were present in 3 of the series and were synchronous in the 2 time series from high altitudes. At low altitude, regime shifts were associated with a shift from increasing to decreasing malaria transmission, as well as a decrease in variability. At higher altitudes, regime shifts reflected an increase in malaria transmission variability. The heterogeneity in malaria trends probably reflects the multitude of factors that can drive malaria transmission and highlights the need for both spatially and temporally fine-grained data to make sound inferences about the impacts of climate change and control/elimination interventions on malaria transmission.     

Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands

Introduction

Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies.

Methods and Findings

A conceptual model of potential malaria risk factors in the highlands was built based on the available literature. Furthermore, the relative importance of these factors on malaria can be estimated through “classification and regression trees”, an unexploited statistical method in the malaria field. This CART method was used to analyse the malaria risk factors in the Burundi highlands. The results showed that Anopheles density was the best predictor for high malaria prevalence. Then lower rainfall, no vector control, higher minimum temperature and houses near breeding sites were associated by order of importance to higher Anopheles density.

Conclusions

In Burundi highlands monitoring Anopheles densities when rainfall is low may be able to predict epidemics. The conceptual model combined with the CART analysis is a decision support tool that could provide an important contribution toward the prevention and control of malaria by identifying major risk factors.     

Malaria control: achievements, problems and strategies

Even if history has not always been the Magistra vitae, Cicero expected it to be, it should provide, as Baas said, a mirror in which to observe and compare the past and present in order to draw therefrom well-grounded conclusions for the future. Based on this belief, this paper aims to provide an overview of the foundations and development of malaria control policies during the XX century. It presents an analysis of the conflicting tendencies which shaped the development of these policies and which appear to have oscillated between calls for frontal attack in an all-out campaign and calls for sustainable gains, even if slow. It discusses the various approaches to the control of malaria, their achievements and their limitations, not only to serve as a background to understand better the foundations of current policies, but also to prevent that simplistic generalisations may again lead to exaggerated expectations and disillusion. The first part of the paper is devoted to the development of malaria control during the first half of the century, characterised by the ups and downs in the reliance on mosquito control as the control measure applicable everywhere. The proliferation of "man-made-malaria", which accompanied the push for economic development in most of the endemic countries, spurred the need for control interventions and, while great successes were obtained in many specific projects, the general campaigns proposed by the enthusiasts of vector control faced increasing difficulties in their practical implementation in the field. Important events, which may be considered representative of this period are, on the campaign approach, the success of Gorgas in the Panama Canal, but also the failure of the Mian Mir project in India; while on the developmental approach, the Italian and Dutch schools of malariology, the Tennessee Valley and the development of malaria sanitation, included the so called species sanitation. The projection of these developments to a global scale was steered by the Malaria Commission of the League of Nations and greatly supported by the Rockefeller Foundation. Perhaps the most important contribution of this period was the development of malaria epidemiology, including the study of the genesis of epidemics and their possible forecasting and prevention. Although the great effectiveness of DDT was perhaps the main determinant for proposing the global eradication of the disease in the 1950s, it was the confidence in the epidemiological knowledge and the prestige of malariology, which gave credibility to the proposal at the political level. The second part deals with the global malaria eradication campaign of the 1950s and 1960s. It recognises the enormous impact of the eradication effort in the consolidation of the control successes of the first half of the century, as well as its influence in the development of planning of health programmes. Nevertheless, it also stresses the negative influence that the failure to achieve its utopian expectations had on the general disappointment and slow progress of malaria control, which characterised the last third of the century. The paper then analyses the evolution of malaria control funding, which often appears out of tune with political statements. The fourth part is devoted to the search for realistic approaches to malaria control, leading to the adoption of the global malaria control strategy in Amsterdam in 1992, and the challenge, at the end of the century, to rally forces commensurate with the magnitude of the problem, while aiming at realistic objectives. After discussing the conflicting views on the relations between malaria and socio-economic development and the desirable integration of malaria control into sustainable development, the paper ends with some considerations on the perspectives of malaria control, as seen by the author in early 1998, just before the launching of the current Roll Back Malaria initiative by WHO.     

Mosquitoes and transmission of malaria parasites – not just vectors

The regional malaria epidemics of the early 1900s provided the basis for much of our current understanding of malaria epidemiology. Colonel Gill, an eminent malariologist of that time, suggested that the explosive nature of the regional epidemics was due to a sudden increased infectiousness of the adult population. His pertinent observations underlying this suggestion have, however, gone unheeded. Here, the literature on Plasmodium seasonal behaviour is reviewed and three historical data sets, concerning seasonal transmission of Plasmodium falciparum, are examined. It is proposed that the dramatic seasonal increase in the density of uninfected mosquito bites results in an increased infectiousness of the human reservoir of infection and, therefore, plays a key role in "kick-starting" malaria parasite transmission.     

Climate variability and malaria epidemics in the highlands of East Africa

Malaria epidemics in the highlands of East Africa garner significant research attention, due, in part, to their proposed sensitivity to climate change. In a recent article, Zhou et al. claim that increases in climate variance, rather than simple increases in climate mean values, have had an important role in the resurgence of malaria epidemics in the East African highlands since the early 1980s. If proven, this would be an interesting result but we believe that the methods used do not test the hypothesis suggested.     

Malaria vaccines: immunity, models and monoclonal antibodies

Although experts in the field have agreed on the malaria vaccine technology roadmap that should be followed (http://www.malariavaccineroadmap.net/), the path towards an effective malaria vaccine remains littered with intellectual and practical pot-holes. The animal models that are currently available are problematic, and current understanding of the exact mechanisms and targets of protective immune responses is incomplete. However, recent technological advances might help overcome some of these hurdles.     

Non-stochastic and stochastic linear indices of the 'molecular pseudograph's atom adjacency matrix': application to 'in silico' studies for the rational discovery of new antimalarial compounds

Malaria is one of the most deadly diseases, affecting million of people especially in developing countries. Because of the rapidly increasing threat worldwide of malaria epidemics multidrugs resistant to therapies, there is an urgent global need to discover new classes of antimalarial compounds. In an effort to overcome this problem, we have investigated the use of structure-based classification models for the 'rational' selection/identification or design/optimization of new lead antimalarials from virtual combinatorial data sets. In this sense, TOpological MOlecular COMputer Design strategy (TOMOCOMD approach) has been introduced in order to obtain two quantitative models for the discrimination of antimalarials. A collected data set containing 597 antimalarial compounds is presented as a helpful tool not only for theoretical chemist but for other researchers in this area. The validated models (including non-stochastic and stochastic indices) classify correctly more than 90% of compounds in both training and external prediction data sets. They showed high Matthews' correlation coefficients; 0.87 and 0.82 for training and 0.86 and 0.79 for test set. The TOMOCOMD-CARDD approach implemented in this work was successfully compared with two of the most useful models for antimalarials selection reported so far. Thus we expect that these two QSAR models can be used in the identification of previously un-known antimalarials compounds.     

The last and the next hundred years of malariology

The founding fathers of malariology combined scientific originality, perseverance in research, strong characters, breadth of interest and social concern. A hundred years later research and understanding has made immense progress but the world still bears a huge burden of malaria. For the next century research requires both more specialism and a holistic range if it is to be used in control, requiring multidisciplinary team work. Environmental changes and interventions produce a dynamic and changing pattern of malaria, not the static one of the past. From the original parasite life cycle, research has analysed a series of other cycles at electron microscope, biochemical and genome levels on decreasing size scales and quantitative epidemiological cycles for control. Recent additions to these concepts have been stage-specific antigens, cycles of disease rather than parasites alone, considering populations of parasites rather than just cases, and also genetic variation in each component of the parasite-human host-vector triad. In this volume there emerges for the first time a coherent overall picture of the biomedical aspects of basic malariology as the interacting population genetics of malaria parasites, anophelines and people. This provides a coherent model for the new century dealing with the great biological malaria problems of drug resistance, vaccine development, insecticidal and net control and can feed, with socio-economic work, into the gathering renewal of control efforts. New work on large-scale changes of malaria in space and time enables us to be precise about effects of local and global environmental changes to predict epidemics. Future research will be as much about linking these different scales of understanding as control will be about linking different levels of the health system. The grim situation in poor holoendemic countries also requires practical support of the type that the founders of malariology were involved in. A coherent understanding needs to feed into the new control efforts, from Roll Back Malaria onwards, for the next century.     

Incidence patterns of vivax malaria in civilians residing in a high-risk county of Kyonggi-do (province), Republic of Korea.

The characteristics of vivax malaria epidemics along the demilitarized zone (DMZ) in the Republic of Korea has been established by the early surveillance data. To further characterize the epidemic, data of civilian patients microscopically diagnosed with malaria from 1995 through 2000 were analyzed in Yonchon-gun (county). Malaria incidence was greater in male civilians > 30 years of age (p < 0.05). The annual parasite index was significantly higher in those living in the administrative areas (Myeon) traversed by DMZ than those living in Myons not traversed by DMZ (p < 0.05). Analysis according to the distance (4 to 14 km) from DMZ showed that people living in villages close to DMZ had higher annual parasite indices than those living in villages remote from DMZ (p for trend < 0.05). Civilians living in Myeons with plains and located in northwestern part of the county had higher annual parasite indices than those living in hilly Myeons located in southeastern part of the county (p for trend < 0.05). These findings suggest that the contraction of vivax malaria is related with night-time outdoor activities, and that the distance from DMZ is a risk factor. In this area, the flying distance of infected vector mosquitos can explain the annually repeating occurrence of civilian cases.     

Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia

ABSTRACT: BACKGROUND: Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. METHODS: In this study seasonal auto regressive integrated moving average (SARIMA) models were used to quantify the relationship between malaria cases and remotely sensed environmental variables, including rainfall, land-surface temperature (LST), vegetation indices (NDVI and EVI), and actual evapotranspiration (ETa) with lags ranging from one to three months. Predictions from the best model with environmental variables were compared to the actual observations from the last 12 months of the time series. RESULTS: Malaria cases exhibited positive associations with LST at a lag of one month and positive associations with indicators of moisture (rainfall, EVI and ETa) at lags from one to three months. SARIMA models that included these environmental covariates had better fits and more accurate predictions, as evidenced by lower AIC and RMSE values, than models without environmental covariates. CONCLUSIONS: Malaria risk indicators such as satellite-based rainfall estimates, LST, EVI, and ETa exhibited significant lagged associations with malaria cases in the Amhara region and improved model fit and prediction accuracy. These variables can be monitored frequently and extensively across large geographic areas using data from earth-observing sensors to support public health decisions.