Climate OMaWa Uncategorized

Malaria and Temperature

How malaria models relate temperature to malaria transmission



It is well known that temperature has a major influence on the transmission of malaria parasites to their hosts. However, mathematical models do not always agree about the way in which temperature affects malaria transmission.


In this study, we compared six temperature dependent mortality models for the malaria vector Anopheles gambiae sensu stricto. The evaluation is based on a comparison between the models, and observations from semi-field and laboratory settings.


Our results show how different mortality calculations can influence the predicted dynamics of malaria transmission.


With global warming a reality, the projected changes in malaria transmission will depend on which mortality model is used to make such predictions.


Parasites & Vectors 2013, 6:20


Do bed nets only give personal protection?

A study by Loha and colleges in Plos One looked at the effect of IRS and ITNs in a village in Southern Ethiopia:

The level of ITN utilization increased after mass distribution of ITNs; however it did not lower the risk for malaria clustering. Therefore, it is possible that free mass distribution of ITNs is not an effective tool with which to combat malaria without follow-up to ensure the optimal utilization of the ITNs.


Of course, there are several studies showing the effect of bed net usage on community malaria incidence, but there is a lack of studies showing the effectiveness of ITNs dependent on the involved vector. In the study are Anopheles arabiensis is the dominant vector, a mosquito which feed indoor as well as outdoor, and possibly before people go to bed.


Perceptions of malaria: implications for control

This week Dori et al. published an interesting study about perceptions of malaria in the Konso community in Ethiopia:


Using a structured questionnaire, focus group discussions and in-depth interviews, this study aimed to gain deeper insight on how the Konso community in Ethiopia perceives malaria and manages the disease. Although knowledge about malaria was above average it surfaced that the use of herbal home remedies is widespread. It is argued that this practice warrants further investigation to validate the efficacy and safety of plant preparations that are employed.


The MW-journal was new to me. It is as open access journal which does not charge the authors (or the readers) for publishing articles. It will be interesting to see if the community embraces this journal, and if it is a threat to Malaria Journal.



In order to work with netcdf-data and at the same time use sp-methods in R it is convenient to have a spatial format that supports time. A new R format, Spatial3dArray might be one way to deal with these kind of data. To use the new class you have to load sp.

setClass( "Spatial3dArray",
          representation("Spatial", data = "array", coords = "list",
                          time = "character", btime = "character"),
          prototype= list(data = array(NA, c(1,1,1,1)),
                          proj4string = CRS(as.character(NA)),
                          coords = list(1,1),
                          time = "posix",
                          btime = "posix"))

An example on a new Spatial3dArray can be:

x <- matrix(seq(-10, 10, length = 150), 150, 150,
            byrow = FALSE)
y <- matrix(seq(-10, 10, length = 150), 150, 150,
            byrow = TRUE)

tm <- 1:10
tm.c <- as.character(seq(as.POSIXct("2002-01-01 06:00:00",
                                    "2002-01-01 15:00:00"),

z <- array(NA, c(dim(x)[1], dim(x)[2], length(tm.c), 1))

for (i in 1:10) {
a <- c(seq(1,6), rev(seq(2,5)))[i]
b <- c(seq(1, 2, length.out = 5), rev(seq(1, 2, length.out = 5)))
z[,,i,] <- a/10 * ( sin(sqrt((x*b[i])^2+(y*b[i])^2)))

sin3dA <- new("Spatial3dArray",
      data = z,
      coords = list(x, y),
      bbox = matrix(c(min(x), min(y), max(x), max(y), 2, 2), 2, 2,
      dimnames = list(NULL, c("min","max"))),
      time = tm.c,
      btime = c(min(tm.c), max(tm.c)))

dimnames(slot(sin3dA, "data")) = list(NULL,
                                      slot(sin3dA, "time"),
names(slot(sin3dA, "coords")) <- c("x", "y")

Now usual spatial methods can be used to retrieve bbox and proj4string. Since Spatial3dArray stores coordinates in a different way then the usual sp-objects we have to define a new function to get the coordinates (a list with two matrices):

coordinates.3dArray <- function (obj, type = "list") {
  if (is(obj, "Spatial3dArray")) {
  lat <- slot(obj, "coords")[[1]]
  long <- slot(obj, "coords")[[2]]
  if (type == "list") {
    return(list(lat=lat, long=long))
    } else if (type == "sp") {
        res <- as.matrix(cbind(c(long), c(lat)))
        dimnames(res) <- list(NULL, c("x1", "x2"))
setMethod("coordinates", signature("Spatial3dArray"), coordinates.3dArray)

So plotting with lattice wireframe and Graphics Magic would give something like:

Sinus animation

I will come back with more methods related to the Spatial3dArray.


Downscaling – progress

It seems like we are getting the grip on both dynamical downscaling and running things to the supercomputer. At the moment we are running the model for one week (2005 data). Tomorrow morning we expect the computations to finish. Then, once again, it is time to break everything and feed the model with even more data. I guess that is how it works; once you have something that is working, the fun is gone, and you have to make improvements which likely will ruin the setup.


Starting a research blog

About the site

This page will host information about Open Malaria Warning (OMaWa). OMaWa is a child of EMaPS (Ethiopian Malaria Prediction System), and the model will also be used in a recent project funded by ESA (European Space Agency). All models and source code will be released under GPL >=2 license once they have been published. Information on where to get the source code will be posted once the distribution system is ready (svn and track).

About me

I am currently a PhD student at Center for International Health/Geophysical Institute at the University of Bergen, Norway. My supervisors are Professor Bernt Lindtjørn and Ass. professor Asgeir Sorteberg. You can read more about the project at the EMaPS web pages. Information about me can be found here.