A new study in Scientific Reports show that diurnal temperature fluctuations are important for a correct description of the dynamics of malaria in the real world. This is a nice addition to the previous work by Paaijmans, and once again it has been shown malaria models should not be oversimplified. Although we are getting closer to understanding how temperature influence malaria transmission, there are still many unresolved questions. In the srep article the authors also show how indoor temperature differ from outdoor temperature, and how this change malaria transmission. I totally agree this is an important factor, even though I do not agree on the functional form of the indoor-outdoor temperature relationship (see MJ article). Anyway, nice work, nicely written. Discussion is a must-read.
Month: February 2013
A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. II. Validation of species distribution and seasonal variations
Background
The first part of this study aimed to develop a model for Anopheles gambiae s.l. with separate parametrization schemes for Anopheles gambiae s.s. and Anopheles arabiensis. The characterizations were constructed based on literature from the past decades. This part of the study is focusing on the model’s ability to separate the mean state of the two species of the An. gambiae complex in Africa. The model is also evaluated with respect to capturing the temporal variability of An. arabiensis in Ethiopia. Before conclusions and guidance based on models can be made, models need to be validated.
Methods
The model used in this paper is described in part one (Malaria Journal 2013, 12:28). For the validation of the model, a data base of 5,935 points on the presence of An. gambiae s.s. and An. arabiensis was constructed. An additional 992 points were collected on the presence An. gambiae s.l.. These data were used to assess if the model could recreate the spatial distribution of the two species. The dataset is made available in the public domain. This is followed by a case study from Madagascar where the model’s ability to recreate the relative fraction of each species is investigated. In the last section the model’s ability to reproduce the temporal variability of An. arabiensis in Ethiopia is tested. The model was compared with data from four papers, and one field survey covering two years.
Results
Overall, the model has a realistic representation of seasonal and year to year variability in mosquito densities in Ethiopia. The model is also able to describe the distribution of An. gambiae s.s. and An. arabiensis in sub-Saharan Africa. This implies this model can be used for seasonal and long term predictions of changes in the burden of malaria. Before models can be used to improving human health, or guide which interventions are to be applied where, there is a need to understand the system of interest. Validation is an important part of this process. It is also found that one of the main mechanisms separating An. gambiae s.s. and An. arabiensis is the availability of hosts; humans and cattle. Climate play a secondary, but still important, role.
Weather is important for transmission of malaria. The simplest way to measure the current weather is to walk outside and feel whether it is cold or hot, and see if it is sunny, cloudy, or rainy. Weather and climate models always start with a measurement of the current weather. Rather than relying on the perceived conditions, the weather models need accurate observations of the current weather. Such observations can be derived from satellites measuring the temperature, pressure, winds, and vapour content of the atmosphere. In addition, weather balloons can be used to correct the satellite derived observations. Once the current weather has been measured, these observations can be used as initial conditions in climate and weather models, and weather can be foretasted up to ten days ahead. With additional information about the temperature, density and salinity of the ocean, weather can be projected a season ahead. If you add volcanoes, variability of the sun, and greenhouse gasses, it is possible to estimate historical and future weather and climate.
Independent on which time period is of interest, these forecasts, or projections, have to be cover the entire Earth, and the forecasts involves solving millions of equations which demands computational resources. To keep the cost down, the global models are often run with a coarse resolution, dividing the Earth into squares of 250 km x 250 km. In regions where the land is flat for several thousand kilometres, and there is no ocean nearby, these coarse resolutions may be good enough to simulate the weather. Once a mountain, coastline, different land use, or soil types are present, the coarse global models represents the weather poorly. To aid this problem, one can use regional climate models (RCMs).
Regional climate models work by increasing the resolution of the global models in a smaller area, a domain, of interest. Such domain might cover southern Africa, Ethiopia, or western Africa, and resolve the terrain down to one by on km. The global climate model determines the large scale winds, temperatures, pressure, and humidity entering the smaller domain. The regional climate model can then resolve the local impact on weather from land use, orography, soil types etc., giving weather and climate information at much finer resolutions that what is feasible using a global model.
Categories
Discovery of new Monkey
Only a few months after the discovery of a new species of monkey has been identified in Africa, yet a new species hit the surface. It was during a visit to the deep forests of DR Congo, close to the Lomami river (the same area as the previous discovery) we ran into a colony of the newly discovered species. The colony consisted of one individual. Unfortunately all documentation in form of photography were lost in the river on the journey back to Kinshasha, so you have to rely on our research notes, analysis done in the field, and our memory. We hope the new journal PeerJ will accept our publication based on the limited material.
Summary of Materials and Methods
A notebook, a faint memory, a lost camera, and a standard RGBA test.
Results
Pigmentation
Before loosing the camera, we were able to carry out a RGBA test accurately describing the pigmentation of the monkey.
Hair: 5494d2ff
Skin: d9e9f9ff
Ear skin: ffd4aaff
These are rather unusual colours, and might result from our research assistant being obsessed with camera filters, and suffering from loss of short time memory thus being unable to recall if any filters were applied at the time of taking the pictures. Since the ear skin has reasonable colours, we conclude he did not apply any filters, and that the RGBA analysis show the true colours.
Behaviour and anatomy
The most stunning feature of this new monkey is the lack of knees, quite unusual for monkeys which are known to spend considerable time in trees. The head is disproportionally large, and it surprised us how the neck was able to support the weight of the massive cranium. The torso is water drop shaped, and resembles the one of a penguin. Given that the monkey is living close to a river, and the obscure anatomy, we speculate this monkey is spending most its time in water, where supporting the weight of the head would not be a problem, and the lack of knees would be beneficial for swimming performance. At the time of observation it was however sitting quietly, and alone, at the river bank, playing with some research equipment our assistant had forgotten when taking water samples the previous day.
Conclusions
We have discovered a single water living, blue monkey in DR Congo. Probably it is mainly feeding on fish, but this needs to be confirmed by an expensive research project, hopefully lasting several years. Since there are some weaknesses regarding the documentation, we hope naming the new species after the founders of PeerJ, Binfield and Hoyt, will ease the review process. We propose the monkey should be named Aquavivens toybin, or Aquavivens toJbin since toybin already has a twitter account.
#PeerJMonkey
A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. I. Model description and sensitivity analysis
Background
Most of the current biophysical models designed to address the large-scale distribution of malaria assume that transmission of the disease is independent of the vector involved. Another common assumption in these type of model is that the mortality rate of mosquitoes is constant over their life span and that their dispersion is negligible. Mosquito models are important in the prediction of malaria and hence there is a need for a realistic representation of the vectors involved.
Results
We construct a biophysical model including two competing species, Anopheles gambiae s.s. and Anopheles arabiensis. Sensitivity analysis highlight the importance of relative humidity and mosquito size, the initial conditions and dispersion, and a rarely used parameter, the probability of finding blood. We also show that the assumption of exponential mortality of adult mosquitoes does not match the observed data, and suggest that an age dimension can overcome this problem.
Conclusions
This study highlights some of the assumptions commonly used when constructing mosquito-malaria models and presents a realistic model of An. gambiae s.s. and An. arabiensis and their interaction. This new mosquito model, OMaWa, can improve our understanding of the dynamics of these vectors, which in turn can be used to understand the dynamics of malaria.
A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. I. Model description and sensitivity analysis