Linking measures of governance to infectious disease indicators

The attempt to demonstrate quantitatively a link between governance factors and a more narrow measure of infectious disease risk in particular has been more challenging, in part because infectious disease risk is not spread evenly across populations, and comparisons between countries of the prevalence of a specific disease miss the over-burdening of some communities or subgroups within a country. In addition, governance influences different infectious disease risks in different ways, and presents distinct challenges to governments - compelling different types of government policies and approaches. For example, the risks posed by mosquito-borne diseases such as malaria or dengue fever present different possibilities for spread and control than, for example, hepatitis B or C, which are transmitted through sex or blood contact.

Nonetheless, the belief that there is a link between governance and specific infectious disease spread stems from an understanding that how governments handle infectious disease is determined not just by epidemiologic characteristics, but also by the overall political and social climate of the nation. Experience shows, for example, that the response to infectious disease epidemics will be strongly influenced to the detriment of the public health by the level of social opprobrium against the populations affected, by social discomfort with the means of transmission implicated (such as drug use or sex), and by fear and ignorance surrounding the disease or its means of transmission. These factors may make it important for governments to address infectious disease spread through working respectfully with at-risk populations, rather than adopting top-down approaches (such as criminalizing disease transmission, instituting mandatory testing, and quarantining people living with infectious diseases) that risk driving these populations even further to the margins of society where they cannot be reached with prevention services.

The theoretical basis for this observation is built upon the pioneering work of Jonathan Mann and Paul Farmer, who were among the first to describe the impact of human rights violations on health. Mann argued that pervasive human rights abuses perpetrated against socially marginalized groups (e.g. sexual violence, discrimination, police abuse) increased their risk of acquiring HIV, and that coercive public health responses such as quarantining and forced testing served to drive these groups further into hiding and fuel the epidemic (Mann, 1999). Informed by years of delivering HIV care in Haiti, Paul Farmer used the term "structural violence" to describe conditions of poverty, sexism, racism, and political violence that constrain individuals' ability to make informed and autonomous choices about their health (Farmer, 1999; Farmer, 2004).

Since 2001, the HIV/AIDS and Human Rights Program at Human Rights Watch has gathered thousands of testimonies from persons living with and at high risk of HIV, documenting the link between human rights abuses against them and their risk of HIV. These abuses have included rape, domestic violence, sex discrimination, and other abuses against women and girls; arbitrary arrest, beatings, torture, and the over-incarceration of injecting drug users, gay and bisexual men, sex workers, and other vulnerable groups; arbitrary detention of AIDS activists and outreach workers; and censorship of science-based HIV/AIDS information (Human Rights Watch, 2006b).

One of the first attempts to explain quantitatively the link between a specific infectious disease and governance factors was the study conducted by Menon-Johansson (2005) using World Bank governance indicators to examine HIV prevalence in 149 countries (see Table 15.1). The study found a significant negative correlation between HIV prevalence and all six governance dimensions (r ranged from 0.12 to 0.20, and P ranged from 0.03 to 0.001). The study, though statisti-

Table 15.1 HIV prevalence correlations for each governance dimension and mean governance

Governance dimension

Correlation coefficient (n = 149)

P value

Voice and accountability

-0.123

0.032

Political stability and absence

-0.164

0.004

of violence

Government effectiveness

-0.204

0.000

Regulatory quality

-0.157

0.006

Rule of law

-0.194

0.001

Corruption

-0.184

0.001

Mean governance

-0.170

0.003

Source: Menon-Johansson etal. (2005); original publisher, Biomed Central.

Source: Menon-Johansson etal. (2005); original publisher, Biomed Central.

cally significant, suggested that governance accounted for only a small percentage of the variance in HIV prevalence from one country to the next.

To address the relatively weak correlation found by Menon-Johansson (2005), Reidpath and Allotey (2006) re-analyzed the data using a single composite indicator from the six governance dimensions provided by the World Bank. The authors found a similar result (r = 0.2, P < 0.05), and concluded that analyzing structural measures such as governance versus single diseases was bound to show a weaker correlation than broader measures unless the diseases were ubiquitous. However, the authors say little about the limitations inherent in comparing across countries an infectious disease such as HIV that is manifested in different communities (because of different frequencies of dominant risk behaviors) and was introduced at different times into different communities and countries. As HIV is still a relatively newly introduced infection in many countries, measurements assessing current HIV prevalence versus governance may as yet be inappropriate. The dynamics of the global HIV epidemic are still fluid and, particularly in Eastern Europe and Asia, future prevalence is uncertain, making an analysis using current prevalence an uneven comparison.

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