Epidemiology in the strategies for malaria control

A rapid overview is presented of the evolution of the main orientations of malaria control, since the discovery of mosquito transmission. Stated control objectives appear to have oscillated between expectations to eradicate the vector, or at least the disease, and more modest approaches to minimise the effects of the infection. High optimism was raised when a new control measure, or new combination of existing measures, appeared to be highly effective and was expected to have universal applicability. The implementation of large scale campaigns eventually found the limits of applicability of the proposed strategy and the exaggerated expectations soon gave way to disillusion and, eventually, to a revival of research. The longest and most impacting period of exaggerated expectations was the global malaria eradication campaign of the 1950s and 1960s, which completely disregarded the study of local epidemiology, considering that all it was needed was to know if an area was "malarious" or not. Research was practically abandoned and, even when reinstated after the recognised failure of the campaign, it has retained an almost exclusive orientation towards the development of control tools, drugs or eventually vaccines. One of the earliest victims of the eradication campaign was the study of epidemic malaria and its determinants in different epidemic prone areas. In spite of an extremely long period of disillusion, lasting for almost two decades, the reality of the malaria problem led WHO and member countries to agree on a global strategy of control, aiming at a realistic use of existing tools, to at least reduce or prevent mortality. An essential element of this strategy is the prevention or control of malaria epidemics and the selective use of vector control, both of which have to be based on a solid knowledge of local epidemiology, the study of which has to rejoin the path abandoned fifty years ago.     

Forecasting and prevention of epidemic malaria: new perspectives on an old problem

There is a clear need for improved epidemic malaria surveillance mechanisms in areas prone to the disease. Epidemiological surveillance systems are rarely able to provide information in a sufficiently timely manner for adequate epidemic response. This is especially true in African countries where surveillance is poorly developed, and particularly so in remote regions of unstable malaria such as desert fringes. There is long standing evidence linking climatic variability and epidemic risk. The last ten years have seen significant developments in Environmental Information System (EIS) for a range of natural resource management purposes. The routine information products from these systems have been shown to be both spatially and temporally related to malaria transmission indicators across the African continent. EIS may therefore provide a useful and cost effective input to epidemic malaria control planning and response.     

Application of Geographical Information Systems and Remote Sensing technologies for assessing and monitoring malaria risk

Despite over 30 years of scientific research, algorithm development and multitudes of publications relating Remote Sensing (RS) information with the spatial and temporal distribution of malaria, it is only in recent years that operational products have been adopted by malaria control decision-makers. The time is ripe for the wealth of research knowledge and products from developed countries be made available to the decision-makers in malarious regions of the globe where this information is urgently needed. This paper reviews the capability of RS to provide useful information for operational malaria early warning systems. It also reviews the requirements for monitoring the major components influencing emergence of malaria and provides examples of applications that have been made. Discussion of the issues that have impeded implementation on a global scale and how those barriers are disappearing with recent economic, technological and political developments are explored; and help pave the way for implementation of an integrated Malaria Early Warning System framework using RS technologies.     

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.     

Genetic effects of human migrations and isolation

This paper analyses how migrations, environment and epidemics interact to shape genetic variation in the moder human species. The gene mutation that makes humans resistant to malaria is a striking example of how disease can shape the human genome. In Europe malaria spread in coincidence with the arrival of populations from Asia Minor and eastern Mediterranean and was favoured by the spread of agriculture, by the sedentary conditions of life and the related demographic increase. Natural selection, generally, shape the gene pool of a population in order to fit a different environment. This is the reason because hemoglobinopathies and enzyme G6PD deficit are greatly spread in areas hit by malaria epidemic. These effects are particularly evident in isolated regions or in islands with low population density, e.g. Sardinia. Disasters such as epidemics may drastically reduced the size of a population, and the victims under such circumstances are not selected. As a result the survivors within this small population are unlikely to be representative of the original population in its genetic makeup, and this occurrence is known as “bottleneck effect”. Sardinia, for instance, was hit between 1300 and 1700 by several plague epidemics. Such events drastically reduced the total number of inhabitants; creating a local alteration in the gene frequencies, that have moulded the genetics of the population. This has brought about not only a differentiation with respect to other Mediterranean populations, but creating a variability inside the island.     

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.     

Expressed sequence tags (ESTs) from immune tissues of turbot (Scophthalmus maximus) challenged with pathogens

Background  

In the recent past, the introduction of Classical Swine Fever Virus (CSFV) followed by between-herd spread has given rise to a number of large epidemics in The Netherlands and Belgium. Both these countries are pork-exporting countries. Particularly important in these epidemics has been the occurrence of substantial "neighborhood transmission" from herd to herd in the presence of base-line control measures prescribed by EU legislation. Here we propose a calculation procedure to map out "high-risk areas" for local between-herd spread of CSFV as a tool to support decision making on prevention and control of CSFV outbreaks. In this procedure the identification of such areas is based on an estimated inter-herd distance dependent probability of neighborhood transmission or "local transmission". Using this distance-dependent probability, we derive a threshold value for the local density of herds. In areas with local herd density above threshold, local transmission alone can already lead to epidemic spread, whereas in below-threshold areas this is not the case. The first type of area is termed 'high-risk' for spread of CSFV, while the latter type is termed 'low-risk'.     

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.     

Anti-malarial drugs and the prevention of malaria in the population of malaria endemic areas

Anti-malarial drugs can make a significant contribution to the control of malaria in endemic areas when used for prevention as well as for treatment. Chemoprophylaxis is effective in preventing deaths and morbidity from malaria, but it is difficult to sustain for prolonged periods, may interfere with the development of naturally acquired immunity and will facilitate the emergence and spread of drug resistant strains if applied to a whole community. However, chemoprophylaxis targeted to groups at high risk, such as pregnant women, or to periods of the year when the risk from malaria is greatest, can be an effective and cost effective malaria control tool and has fewer drawbacks. Intermittent preventive treatment, which involves administration of anti-malarials at fixed time points, usually when a subject is already in contact with the health services, for example attendance at an antenatal or vaccination clinic, is less demanding of resources than chemoprophylaxis and is now recommended for the prevention of malaria in pregnant women and infants resident in areas with medium or high levels of malaria transmission. Intermittent preventive treatment in older children, probably equivalent to targeted chemoprophylaxis, is also highly effective but requires the establishment of a specific delivery system. Recent studies have shown that community volunteers can effectively fill this role. Mass drug administration probably has little role to play in control of mortality and morbidity from malaria but may have an important role in the final stages of an elimination campaign.     

Database management system for the control of malaria in Arunachal Pradesh, India

The Arunachal Pradesh state in India is epidemic for malaria, caused by P.vivax and P.falciparum. Despite the implementation of several control strategies, the outbreak of malaria in the state is mainly due to lack of proper information regarding the disease. Hence, we completed a database to help implement appropriate control strategy for the public health officials in Arunachal Pradesh. AVAILABILITY: www.envisiict.org.     

Early detection surveillance for an emerging plant pathogen: a rule of thumb to predict prevalence at first discovery

Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally.     

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.     

Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data

Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. Data describing human mobility and malaria epidemiology can help classify landscapes into parasite demographic sources and sinks, ecological concepts that have parallels in malaria control discussions of transmission foci. By linking transmission to parasite flow, it is possible to stratify landscapes for malaria control and elimination, as sources are disproportionately important to the regional persistence of malaria parasites. Here, we identify putative malaria sources and sinks for pre-elimination Namibia using malaria parasite rate (PR) maps and call data records from mobile phones, using a steady-state analysis of a malaria transmission model to infer where infections most likely occurred. We also examined how the landscape of transmission and burden changed from the pre-elimination setting by comparing the location and extent of predicted pre-elimination transmission foci with modeled incidence for 2009. This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. The changing spatial distribution of burden could be due to importation, with cases focused around importation hotspots, or due to heterogeneous application of elimination effort. While this framework is an important step towards understanding progressive changes in malaria distribution and the role of subnational transmission dynamics in a policy-relevant way, future work should account for international parasite movement, utilize real time surveillance data, and relax the steady state assumption required by the presented model.     

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.     

Current status of vivax malaria among civilians in Korea

A result of national malaria surveillance in Korean civilians was described. Since a case of indigenous vivax malaria was detected in 1993, a total of 2,198 cases was confirmed by blood smear up to 1997. Of them, 1,548 cases were soldiers serving in the demilitarized zone (DMZ), while 650 cases were civilians. Number of civilian cases was 3 in 1994, 19 in 1995, 71 in 1996, and 557 in 1997. Of them, 239 were ex-soldiers who discharged after military service in the prevalent areas such as Paju, Yonchon, Kimpo, Kangwha, Tongduchon in Kyonggi-do and Chorwon in Kangwon-do while 308 patients were civilian residents in the prevalent areas. Seventy-two patients, living nationwide, had a history of visiting the prevalent areas during transmission season. Only 32 civilian patients denied any relation with the prevalent areas. As a whole, a half of the civilian cases was diagnosed when living in non-prevalent areas. Male patients in their twenties was the highest in number. Annual parasite index is steadily elevated in residents living in the prevalent areas. Monthly incidence showed an unimodal distribution, forming a peak in August. Ex-soldiers exhibited a delayed incubation ranging from 153 to 452 days (279 ± 41 days). The time required for diagnosis was shortened from 23.6 days in 1995 to 13.7 days in 1997. Although the current epidemic of vivax malaria started as a border malaria, it seems highly probable that vivax malaria is established in the local areas and responsible for at least a part of transmission.     

Molecular Phylodynamic Analysis Indicates Lineage Displacement Occurred in Chinese Rabies Epidemics between 1949 to 2010

Rabies remains a serious problem in China with three epidemics since 1949 and the country in the midst of the third epidemic. Significantly, the control of each outbreak has been followed by a rapid reemergence of the disease. In 2005, the government implemented a rabies national surveillance program that included the collection and screening of almost 8,000 samples. In this work, we analyzed a Chinese dataset comprising 320 glycoprotein sequences covering 23 provinces and eight species, spanning the second and third epidemics. Specifically, we investigated whether the three epidemics are associated with a single reemerging lineage or a different lineage was responsible for each epidemic. Consistent with previous results, phylogenetic analysis identified six lineages, China I to VI. Analysis of the geographical composition of these lineages revealed they are consistent with human case data and reflect the gradual emergence of China I in the third epidemic. Initially, China I was restricted to south China and China II was dominant. However, as the epidemic began to spread into new areas, China I began to emerge, whereas China II remained confined to south China. By the latter part of the surveillance period, almost all isolates were China I and contributions from the remaining lineages were minimal. The prevalence of China II in the early stages of the third epidemic and its established presence in wildlife suggests that it too replaced a previously dominant lineage during the second epidemic. This lineage replacement may be a consequence of control programs that were dominated by dog culling efforts as the primary control method in the first two epidemics. This had the effect of reducing dominant strains to levels comparable with other localized background stains. Our results indicate the importance of effective control strategies for long term control of the disease.     

Population and Land Use Effects on Malaria Prevalence in the Southern Brazilian Amazon

Malaria prevalence has been one of the most dramatic outcomes of the occupation of the Brazilian Amazon as exemplified by Northern Mato Grosso, one of the areas of highest malaria prevalence in the Americas in the early 1990s. This paper associates the dynamicsof high malaria prevalence in Northern Mato Grosso with three land uses—small-scalegold mining (garimpos), agricultural colonization/cattle ranching (rural), and urban activities—and their related population characteristics, which constitute riskprofiles. Furthermore, spatial proximity and population mobility between (a) garimpos and new rural settlements and (b) older rural settlements or urban areas are key factors explaining malaria diffusion throughout the region. The paper identifies and characterizes populations at high malaria risk and the effects of land use types on malaria diffusion, providing policymakers with information for regional and local policies to control malaria and minimize its effects on Amazonian populations.     

The IPTi Consortium: research for policy and action

The results of a randomized controlled trial in Tanzania suggest that intermittent preventive treatment in infants (IPTi), delivered through the Expanded Program on Immunization, might be a useful approach to controlling malaria in countries where it is endemic. An international consortium of research collaborations, involving the World Health Organization and United Nation's Children's Fund, is now evaluating IPTi in a range of different settings to generate robust and compelling evidence to guide policy. This review summarizes the available information on IPTi and presents the consortium's approach to determining whether IPTi might be a valuable additional strategy in programs to control malaria.     

Risk maps for the spread of highly pathogenic avian influenza in poultry

Devastating epidemics of highly contagious animal diseases such as avian influenza, classical swine fever, and foot-and-mouth disease underline the need for improved understanding of the factors promoting the spread of these pathogens. Here the authors present a spatial analysis of the between-farm transmission of a highly pathogenic H7N7 avian influenza virus that caused a large epidemic in The Netherlands in 2003. The authors developed a method to estimate key parameters determining the spread of highly transmissible animal diseases between farms based on outbreak data. The method allows for the identification of high-risk areas for propagating spread in an epidemiologically underpinned manner. A central concept is the transmission kernel, which determines the probability of pathogen transmission from infected to uninfected farms as a function of interfarm distance. The authors show how an estimate of the transmission kernel naturally provides estimates of the critical farm density and local reproduction numbers, which allows one to evaluate the effectiveness of control strategies. For avian influenza, the analyses show that there are two poultry-dense areas in The Netherlands where epidemic spread is possible, and in which local control measures are unlikely to be able to halt an unfolding epidemic. In these regions an epidemic can only be brought to an end by the depletion of susceptible farms by infection or massive culling. The analyses provide an estimate of the spatial range over which highly pathogenic avian influenza viruses spread between farms, and emphasize that control measures aimed at controlling such outbreaks need to take into account the local density of farms.