Review article The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease

Abstract

This paper reviews the application of remote sensing to the study and control of invertebrate intermediate hosts and vectors for some of the most prevalent of human diseases worldwide. Examples are also taken from studies involving animal diseases that have considerable adverse e ects on human welfare. The current status of remote sensing in epidemiology is assessed and suggestions are made on how, in the future, the two ® elds might be most pro® tably combined.

Correlating Remote Sensing Data with the Abundance of Pupae of the Dengue Virus Mosquito Vector, Aedes aegypti, in Central Mexico

“…Associations reported in the literature show that climate-related variables can be used to predict local abundance and the potential for the expansion of arthropod vectors, such as mosquitoes or ticks [7][8][9][10]. Since field surveys are both costly and time consuming, remote sensing (RS) technology is increasingly used to estimate habitat suitability for a variety of vector species [11][12][13][14]. Temperature and rainfall are the weather parameters of special interest, because they impact both the distribution of suitable vector habitat and the potential for local vector proliferation.…”

Application of Remote Sensing and Geographical Positioning System to Spatial Distribution of Glossina Fuscipes Fuscipes (Diptera: Glossinidae) in Kajo-Keji County South Sudan.

“…It has been therefore demonstrated in the tsetse distribution map (Fly AD and infection rate) that distribution of HAT is associated with the presence or absence of the infected flies. This has become possible to map using the RS and GIS that are able to predict the presence or absence of tsetse species with accuracies (Hay et al,1997). RS data can be used to indicate the presence or absence of vectors of diseases and their parasitic hosts (De la Rocque et al, 2004).The approach developed in this study has proved to be capable of producing valuable information on the geographical distribution of all tsetse species of major medical and veterinary importance (Cecchi et al, 2015).…”

Linking remote sensing, land cover and disease

“…In support of such predictions research has been undertaken in different environments, for different diseases and vectors and with various combinations of imagery and ancillary data (Hugh-Jones and O'Neil, 1986;Hay et al, 1997;Estrada-Peña, 1998). Some thirty years of experience (Cline, 1970) have shown that while the remote sensing of disease is certainly viable (Linthicum et al, 1987;Hugh-Jones, 1991a;Rogers and Williams, 1993) it will not be a robust and reliable epidemiological technique until we have developed a sound understanding of all of the links between remotely sensed data and variables of epidemiological significance.…”

“…Furthermore, since the end product is a thematic map depicting land cover type (e.g., different vegetation types of classes of vegetation amount) it is often desirable to alter the image geometrically to a suitable map projection. Since the temporal dimension of remote sensing can be beneficial, if not essential, to some epidemiological studies (Hugh-Jones, 1989;Riley, 1989;Hay et al, 1997), especially in relation to prediction and control activities (Linthicum et al, 1999), the need to correct the imagery such that one image can be compared to another should be seen as important and fundamental to the use of remotely sensed data. Therefore, as was noted at the end of Section 2.3, the basis for epidemiological research…”

“…For example, where remotely sensed data and disease data are both related to climate (Hugh-Jones, 1991a;Thomson et al, 1996;Hay et al, 1996;1998a). When this is the case researchers have sought to use remote sensing as a direct and instrumental tool (Curran, 1987) to predict and map the location of some of the major diseases affecting human health (Bailey and Linthicum, 1989;Hay et al, 1997;1998b;Malone et al, 1997;Connor, 1999)."Satellite (sensor) images can pinpoint the breeding grounds of the mosquitoes that cause malaria, pick out the tsetse fly's favourite haunts and perhaps even identify places where there is a risk of cholera" (K. Kleiner, 1995, p.9).In support of such predictions research has been undertaken in different environments, for different diseases and vectors and with various combinations of imagery and ancillary data (Hugh-Jones and O'Neil, 1986;Hay et al, 1997;Estrada-Peña, 1998). Some thirty years of experience (Cline, 1970) have shown that while the remote sensing of disease is certainly viable (Linthicum et al, 1987;Hugh-Jones, 1991a;Rogers and Williams, 1993) it will not be a robust and reliable epidemiological technique until we have developed a sound understanding of all of the links between remotely sensed data and variables of epidemiological significance.…”