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Infectious Diseases And Civil Conflict

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To answer the question if infectious diseases influence the risk of civil conflict it is necessary to measure the exposure to infectious disease pathogens and the number of civil conflict incidences. MHV-pathogens are utilized to measure the exposure to infectious diseases. Pathogens can be divided into three different host categories. If only humans can serve as host like with HIV, it is human only. If only animals serve as host, like plague, the pathogen is classified as zoonotic. If both humans and animals can be host, it falls under the category of multi-host pathogens. The transmission of pathogens can be divided into two categories. One being transmission through a vector like mosquitos, malaria is an example, and the other being pathogens like influenza, which are transmitted from human to human.

MHV-pathogens are used because they have some distinct features that make them especially suitable for this analysis. First, they are very hard to control because they use different vectors to spread. Also, the treatment of this kind of pathogens is very difficult, since vaccines are mostly unavailable. For this reasons, MHV-pathogens, apart from malaria, are not eliminated on a greater geographical stage. This means that if a specific pathogen has been present in a country it is most likely still there. Second, MHV-pathogens can only be transmitted from one human to another through specific vectors. Consequently, for a pathogen to be present, a country needs suitable biological and climatological conditions for the vector. For this reason, MHV-pathogens are not much affected by globalisation, since for example migration and trade cannot spread the pathogen to countries that do not provide conditions for the vectors to survive. The third reason that makes this class of pathogens suitable, is that the consequences for the health of effected individuals are serious and often deadly.

Two count indices are constructed to measure the exposure to MHV-pathogens in a country. The first count index measures whether a pathogen has ever been present, if it has been reported or diagnosed, in a country. The twelve different types of MHV-pathogens that this analysis uses are dengue, yellow fever, leishmaniasis visceral, relapsing fever, typhus epidemic, angiomatoses, filariasis-brugia malayi, leishmaniasis (mucocutaneous and cutaneous), malaria, onchocerciasis, trypanosomiasis africanis and trypanosomiasis. A specific number of this pathogens can be detected for each country.

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The data on the number of pathogens in a country comes from the Global Infectious Disease and Epidemiology Online Network (GIDEON) database, where high quality data is available for most countries. The reason for this is, that the health consequences of these pathogens are severe and therefore they are observed closely in the whole world. Moreover, the index only uses data on the presence of a pathogen for two reasons. First, the possible error in measurement is lower than with data on the current state of a pathogen because this form of data is for example dependent on the health system or ongoing conflicts. Second, the data is more comparable since the current state of a country, like a functioning health care system, does not influence the presence of a pathogen.

A disadvantage of only using information on the sole presence of a pathogen is that it also measures single cases like migrants or tourists. Furthermore, this form of measurement does not consider the possibility of eradication. If a pathogen has been present in the past it is measured as present in a country, regardless of eradication. Therefore, the second count index measures whether a pathogen is endemic in at least parts of a country now, according to the GIDEON data. To be classified as endemic by GIDEON, the pathogen must be capable of replicating itself without help.

Since the disadvantages of the first index are mostly counteracted by the distinct features of MHV-pathogens, both indices lead to a high resemblance in their results.

The measurement of civil conflict uses information of the UCDP/PRIO Armed Conflict Data set for the period 1960–2007 (version v4, 2012). This data set is offered by the Peace Research Institute of Oslo (PRIO). The dependent variable is called ‘Civil Wars’. This variable includes armed conflicts within a state, that either account for a minimum of 25 deaths per year or over 1000 deaths over the time of the conflict, that are connected to the violence. Armed conflicts within a state are all conflicts, challenge the compatibility regarding government and/or area with the participation of armed forces between two groups. Moreover, one of this groups must be the governing body of a state. Around 140 countries are included in the used data set. At last, many time invariant and time-varying covariates are used in this analysis. They are utilized as control variables and to check the robustness

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Infectious Diseases And Civil Conflict. (2022, Jun 09). Edubirdie. Retrieved December 5, 2022, from https://edubirdie.com/examples/infectious-diseases-and-civil-conflict/
“Infectious Diseases And Civil Conflict.” Edubirdie, 09 Jun. 2022, edubirdie.com/examples/infectious-diseases-and-civil-conflict/
Infectious Diseases And Civil Conflict. [online]. Available at: <https://edubirdie.com/examples/infectious-diseases-and-civil-conflict/> [Accessed 5 Dec. 2022].
Infectious Diseases And Civil Conflict [Internet]. Edubirdie. 2022 Jun 09 [cited 2022 Dec 5]. Available from: https://edubirdie.com/examples/infectious-diseases-and-civil-conflict/
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