Malaria epidemic early warning and detection in African highlands

Malaria epidemics have long been known to recur in the African highlands. Efforts to develop systems of early warning and detection for epidemics are outlined here with special emphasis on the Highland Malaria Project (HIMAL). This project has been conducting research on the operational implementation of a district-based surveillance and epidemic-monitoring system using a network of sentinel sites in four pilot districts of Kenya and Uganda. The potential use of weather monitoring as well as disease surveillance for effective early warning is being investigated.     

Performance of forecasting,warning and detection of malaria epidemics in the highlands of western Kenya

On the 4th July 2002 a leading national newspaper in Kenya, the Daily Nation, ran the headline 'Minister sounds alert on malaria' in an article declaring the onset of epidemics in the highlands of western Kenya. There followed frequent media coverage with quotes from district leaders on the numbers of deaths, and editorials on the failure of the national malaria control strategy. The Ministry of Health made immediate and radical changes to national policy on treatment costs in the highlands by suspending cost-sharing. Development partners and non-governmental organisations also responded with a large increase in the distribution of commodities (approximately 500,000 US dollars) to support preventative strategies across the western highland region. What was conspicuous by its absence was any obvious effort to predict the epidemics in advance of press coverage.     

The durra complex in the central highlands of Ethiopia

The Eastern Galla of Ethiopia have developed advanced agricultural techniques of rotation, terracing and irrigation with Sorghum vulgare (durra) as the major field crop. Crops of secondary importance in the durra complex are corn (Zea mays’), barley, peanuts, sesame, fieldpeas, beans, and fenugreek.     

Comparing models for early warning systems of neglected tropical diseases

Background

Early warning systems (EWS) are management tools to predict the occurrence of epidemics of infectious diseases. While climate-based EWS have been developed for malaria, no standard protocol to evaluate and compare EWS has been proposed. Additionally, there are several neglected tropical diseases whose transmission is sensitive to environmental conditions, for which no EWS have been proposed, though they represent a large burden for the affected populations.

Methodology/Principal Findings

In the present paper, an overview of the available linear and non-linear tools to predict seasonal time series of diseases is presented. Also, a general methodology to compare and evaluate models for prediction is presented and illustrated using American cutaneous leishmaniasis, a neglected tropical disease, as an example. The comparison of the different models using the predictive R ² for forecasts of “out-of-fit” data (data that has not been used to fit the models) shows that for the several linear and non-linear models tested, the best results were obtained for seasonal autoregressive (SAR) models that incorporate climatic covariates. An additional bootstrapping experiment shows that the relationship of the disease time series with the climatic covariates is strong and consistent for the SAR modeling approach. While the autoregressive part of the model is not significant, the exogenous forcing due to climate is always statistically significant. Prediction accuracy can vary from 50% to over 80% for disease burden at time scales of one year or shorter.

Conclusions/Significance

This study illustrates a protocol for the development of EWS that includes three main steps: (i) the fitting of different models using several methodologies, (ii) the comparison of models based on the predictability of “out-of-fit” data, and (iii) the assessment of the robustness of the relationship between the disease and the variables in the model selected as best with an objective criterion.     

Parameter estimation for models of chaotic time series

We illustrate the inadequacy for chaotic time series data of widely-used dynamical parameter-estimation procedures based on whole-trajectory comparisons (observation-error fitting), using as case studies the record of measles outbreaks in New York City and simulated data generated by the logistic equation. We explore and reject alternative estimation methods based on matching emergent features of strange attractors; specifically, the Lyapunov exponents and the Hausdorff dimension. We show that partial-trajectory comparison methods (process-error fitting) work well when the system state is completely known through the course of the experiment.     

Landscape composition and configuration in the central highlands of Ethiopia

Landscape dynamics are common phenomenon in the human‐dominated environments whereby it can be observed that the composition and configuration between landscape elements change over time. This dynamism brings about habitat loss and fragmentation that can greatly alter ecosystem services at patch, class, and landscape levels. We conducted a study to examine composition and configuration of forested landscape in the central highlands of Ethiopia using satellite images of over a period of four decades, and FRAGSTAT raster dataset was used to analyze fragmentation. Our result showed five land use/land cover (LULC) types in the study area. Cultivated land and settlement land increased at the expense of forestland, shrubland, and grassland. Fragmentation analysis showed the number of patches increased for all LULC types, indicating the level of fragmentation and interspersion. Juxtaposition increased for shrubland, grassland, and cultivated lands and decreased for settlement and forestland resulting in the fragmentation and isolation of patches. The study of LULC along with fragmentation at the landscape level can help improve our understanding of the pace at which conversion of landscape elements is happening and the impacts on ecosystem services as studies of LULC are courser in nature and would not show how each land use is reducing in size, proximity and shape among other things that determine ecosystem services. Such type of studies in rural landscapes are very vital to consider appropriate land management policies for the landscape level by taking into account the interaction between each element for sustainable development. We recommend land managers, conservationists, and land owners for observing the roles of each patch in the matrix to maximize the benefits than focusing on a single element.     

The ecology of large carnivores in the highlands of northern Ethiopia

The degradation and fragmentation of the northern Ethiopian highlands has resulted in frequent encounters of large carnivores with humans and their livestock. We interviewed 500 randomly selected households to estimate economic impact of livestock predation by spotted hyaena (Crocuta crocuta), leopard (Panthera pardus) and jackal (Canis aureus aureus) in the highlands of northern Ethiopia. The annual mean economic loss per household was approximately U.S.$ 20.2, about 7% of the average annual income of households in the area. Households surveyed reported losses of a total of 3122 livestock to hyaena, leopard and jackal predation over the past 5 years. This loss equated to a total financial loss of U.S.$ 50,381 . Livestock predation incidents of spotted hyaena, leopard and jackal demonstrated that spotted hyaena had a preference for dog, donkey, goat and sheep; leopard for goat, dog and sheep; and jackal for goat and sheep. Livestock predation of spotted hyaena and leopard were mainly during the night. We conclude that assessing depredation problems is important to develop actions for management of either livestock practices or wildlife conservation.     

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.