Risk assessment with regard to the occurrence of malaria in Africa under the influence of observed and projected climate change

Malaria is one of the most serious health problems in the world. The projected climate change will probably alter the range and transmission potential of malaria in Africa. In this study, potential changes in the malaria transmission are assessed by forcing three malaria models with bias-corrected data from ensemble scenario runs of a state-of-the-art regional climate model. The Liverpool Malaria Model (LMM) from the Geography Department of the University of Liverpool is utilised. The LMM simulates the spread of malaria at a daily resolution using daily mean temperature and 10-day accumulated precipitation. The simulation of some key processes has been modified in the model, in order to reflect a more physical relationship. An extensive literature survey with regard to entomological and parasitological malaria variables enables the calibration and validation of a new LMM version. Comparison of this version with the original model exhibits marked improvements. The new version demonstrates a realistic simulation of entomological variables and of the malaria season, as well as correctly reproduces the epidemic poten tial at fringes of endemic malaria areas. Various sensitivity experiments reveal that the LMM is fairly sensitive to values of its required parameters. Effects of climatic changes on the malaria season are additionally verified by the MARA Seasonality Model (MSM). The Garki model finally enables the completion of the malaria picture in terms of the immune status and the infectiousness of different population groups, as well as relative to the age-dependent prevalence structure. In every case three ensemble runs were performed on a 0.5° grid. The LMM was driven for the present-day climate (1960-2000) by bias-corrected data from the REgional MOdel (REMO), with a land use and land cover specified by the Food and Agriculture Organization (FAO). Malaria projections were carried out for 2001-2050 according to the climate scenarios A1B and B1 as well as FAO land use and land cover changes. Garki model runs were subsequently forced by the Entomological Inoculation Rate (EIR) from the LMM. Finally, additional results relative to the malaria season were produced by MSM. For the present-day climate (1960-2000), the highest biting rates are simulated for Equatorial Africa. The malaria runs show a decrease in the malaria spread from Central Africa towards the Sahel. The length of the malaria season is closely related to monsoon rainfall. The model simulations show a marked influence of mountainous areas causing a complex pattern of the spread of malaria in East Africa. The malaria infected population reveals the expected peak in children below an age of about five years. Regions of epidemic malaria occurrence, as defined by the coefficient of variation of the annual parasite prevalence maximum, are found along a band in the northern Sahel. Farther south, malaria occurs more regularly and is therefore characterised as endemic. Epidemic-prone areas are additionally identified at various highland territories, as well as in arid and semi-arid zones of the Greater Horn of Africa. No adequate immune protection of the population was found for these areas. Largely due to land surface degradation, REMO simulates a prominent surface warming and a significant reduction in the annual rainfall amount over most of tropical Africa in either climate change scenario. Assuming no future human-imposed constraints on malaria transmission, changes in temperature and precipitation will alter the future geographic distribution of malaria. In the northern part of sub-Saharan Africa, the precipitation decline will force significant decreases of the malaria transmission in the Sahel. In addition to the withdrawal of malaria transmission along the fringe of the Sahara, the frequency of malaria occurrence will be reduced for several grid boxes of the Sahel. As a result, epidemics in these more densely populated areas will become more likely, in particularly as adults lose their immunity. The level of malaria prevalence farther south will remain stable for most areas. However, the start of the malaria season will be delayed and the transmission is expected to cease earlier. Most pronounced changes in Africa are found for East Africa. Significantly higher temperatures and slightly higher rainfall cause a substantial increase in the season length and parasite prevalence in formerly epidemic-prone areas. Territories formerly unsuitable for malaria will become suitable under the warmer future climate. The simulations indicate changes in the highland epidemic risk. At most grid boxes malaria transmission will stabilise below about 2000 m. At these altitudes the population will improve their immune status. In contrast, malaria will climb to formerly malaria-free zones above these levels enforcing the probability of malaria epidemics

A breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observations

Daily observations of potential mosquito developmental habitats in a suburb of Kumasi in central Ghana reveal a strong variability in their water persistence times, which ranged between 11 and 81 days. The persistence of the ponds was strongly tied with rainfall, location and size of the puddles. A simple power-law relationship is found to fit the relationship between the average pond depth and area well. A prognostic water balance model is derived that describes the temporal evolution of the pond area and depth, incorporating the power-law geometrical relation. Pond area increases in response to rainfall, while evaporation and infiltration act as sink terms. Based on a range of evaluation metrics, the prognostic model is judged to provide a good representation of the pond coverage evolution at most sites. Finally, we demonstrate that the prognostic equation can be generalised and equally applied to a grid-cell to derive a fractional pond coverage, and thus can be implemented in spatially distributed models for relevant vector- borne diseases such as malaria

Mosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africa

An energy budget model is developed to predict the water temperature of typical mosquito larval developmental habitats. It assumes a homogeneous mixed water column driven by empirically derived fluxes. The model shows good agreement at both hourly and daily time scales with 10-min temporal resolution observed water temperatures, monitored between June and November 2013 within a peri-urban area of Kumasi, Ghana. There was a close match between larvae development times calculated using either the model-derived or observed water temperatures. The water temperature scheme represents a significant improvement over assuming the water temperature to be equal to air temperature. The energy budget model requires observed minimum and maximum temperatures, information that is generally available from weather stations. Our results show that hourly variations in water temperature are important for the simulation of aquatic-stage development times. By contrast, we found that larval development is insensitive to sub-hourly variations. Modelling suggests that in addition to water temperature, an accurate estimation of degree-day development time is very important to correctly predict the larvae development times. The results highlight the potential of the model to predict water temperature of temporary bodies of surface water. Our study represents an important contribution towards the improvement of weather-driven dynamical disease models, including those designed for malaria early forecasting systems

Mosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africa

An energy budget model is developed to predict the water temperature of typical mosquito larval developmental habitats. It assumes a homogeneous mixed water column driven by empirically derived fluxes. The model shows good agreement at both hourly and daily time scales with 10-min temporal resolution observed water temperatures, monitored between June and November 2013 within a peri-urban area of Kumasi, Ghana. There was a close match between larvae development times calculated using either the model-derived or observed water temperatures. The water temperature scheme represents a significant improvement over assuming the water temperature to be equal to air temperature. The energy budget model requires observed minimum and maximum temperatures, information that is generally available from weather stations. Our results show that hourly variations in water temperature are important for the simulation of aquatic-stage development times. By contrast, we found that larval development is insensitive to sub-hourly variations. Modelling suggests that in addition to water temperature, an accurate estimation of degree-day development time is very important to correctly predict the larvae development times. The results highlight the potential of the model to predict water temperature of temporary bodies of surface water. Our study represents an important contribution towards the improvement of weather-driven dynamical disease models, including those designed for malaria early forecasting systems

Neutrophil Extracellular Traps Contain Calprotectin, a Cytosolic Protein Complex Involved in Host Defense against Candida albicans

Neutrophils are the first line of defense at the site of an infection. They encounter and kill microbes intracellularly upon phagocytosis or extracellularly by degranulation of antimicrobial proteins and the release of Neutrophil Extracellular Traps (NETs). NETs were shown to ensnare and kill microbes. However, their complete protein composition and the antimicrobial mechanism are not well understood. Using a proteomic approach, we identified 24 NET-associated proteins. Quantitative analysis of these proteins and high resolution electron microscopy showed that NETs consist of modified nucleosomes and a stringent selection of other proteins. In contrast to previous results, we found several NET proteins that are cytoplasmic in unstimulated neutrophils. We demonstrated that of those proteins, the antimicrobial heterodimer calprotectin is released in NETs as the major antifungal component. Absence of calprotectin in NETs resulted in complete loss of antifungal activity in vitro. Analysis of three different Candida albicans in vivo infection models indicated that NET formation is a hitherto unrecognized route of calprotectin release. By comparing wild-type and calprotectin-deficient animals we found that calprotectin is crucial for the clearance of infection. Taken together, the present investigations confirmed the antifungal activity of calprotectin in vitro and, moreover, demonstrated that it contributes to effective host defense against C. albicans in vivo. We showed for the first time that a proportion of calprotectin is bound to NETs in vitro and in vivo

Development of a new version of the Liverpool Malaria Model. II. Calibration and validation for West Africa

<p>Abstract</p> <p>Background</p> <p>In the first part of this study, an extensive literature survey led to the construction of a new version of the <it>Liverpool Malaria Model </it>(LMM). A new set of parameter settings was provided and a new development of the mathematical formulation of important processes related to the vector population was performed within the LMM. In this part of the study, so far undetermined model parameters are calibrated through the use of data from field studies. The latter are also used to validate the new LMM version, which is furthermore compared against the original LMM version.</p> <p>Methods</p> <p>For the calibration and validation of the LMM, numerous entomological and parasitological field observations were gathered for West Africa. Continuous and quality-controlled temperature and precipitation time series were constructed using intermittent raw data from 34 weather stations across West Africa. The meteorological time series served as the LMM data input. The skill of LMM simulations was tested for 830 different sets of parameter settings of the undetermined LMM parameters. The model version with the highest skill score in terms of entomological malaria variables was taken as the final setting of the new LMM version.</p> <p>Results</p> <p>Validation of the new LMM version in West Africa revealed that the simulations compare well with entomological field observations. The new version reproduces realistic transmission rates and simulated malaria seasons are comparable to field observations. Overall the new model version performs much better than the original model. The new model version enables the detection of the epidemic malaria potential at fringes of endemic areas and, more importantly, it is now applicable to the vast area of malaria endemicity in the humid African tropics.</p> <p>Conclusions</p> <p>A review of entomological and parasitological data from West Africa enabled the construction of a new LMM version. This model version represents a significant step forward in the modelling of a weather-driven malaria transmission cycle. The LMM is now more suitable for the use in malaria early warning systems as well as for malaria projections based on climate change scenarios, both in epidemic and endemic malaria areas.</p