Global Health Institute

Sir Isaac Newton’s law of universal gravitation teaches us more than just how two masses attract each other from a distance. His famous equation relates the gravitational force between two objects to their respective masses and the distance separating the objects: 

F = G m1m2 

r2 

Interestingly, an essentially identical equation may be constructed that is capable of approximating migration flows between two locations, but this time as a function of population sizes (or even other measures) and distance separating the two locations. Generally, the equation below is referred to as a gravity model: 

Mij = G PiαPjβ 

rijγ 

where Mij represents the migrant population, Piα represents the population of the origin location (i), Pjβ represents the population of the destination location (j), and rijγ represents the distance between the two locations. G is just a proportionality constant for scaling purposes. α,β and γ are parameters usually estimated from data. 

My work this semester focused on estimating vaccine stockpile quantities for Nipah virus, a zoonotic virus (often transmitted by bats to humans) prevalent in India and Bangladesh. Estimating migration flow is of particular importance in modeling Nipah virus as it dictates how a disease may spread from location to location, via human travel. In turn, this will determine how and where vaccine stockpiles should be allotted. 

Often, data availability can be a barrier to research, since what data are available play a crucial role in what questions can be posed and answered. Thus, it is often necessary to create models that can closely approximate the unavailable data, based on a series of reasonable assumptions. In my case, because data on migration in India and Bangladesh are extremely scarce, a gravity model proved to be useful in providing estimates of population migration at the district level. I had data on district population and distances between districts, but needed to find values for the exponents in the model: α,β,γ. Briefly, the modeling process proceeded with reviewing travel and migration literature to understand how to properly parameterize the gravity model. After coding the model in Python, I tested various reported exponent values and plotted the results. I also attempted to validate my migration population data with summary-level data on migration in India. This served as a reality check to make sure the results were reasonable compared to what was expected. After some adjustments and scaling, the model output yielded promising results. 

In the larger scheme of the project, these migration estimates would feed into a larger model of Nipah virus transmission dynamics that would inform vaccine stockpile distribution. Vaccine stockpiling is an extremely important topic because it is one of our first lines of defense against the rampant spread of an epidemic or pandemic. It essentially puts the concept of prevention as the best form of a cure into practice. Additionally, estimates like these give policy-makers and vaccine manufacturers concrete, quantitative information on how to prepare for and prevent the spread of disease. 

Andrew Tiu (NHS `21) is an undergraduate studying human science and statistics. He is a student fellow with the Global Health Initiative.

The right to health has received widespread recognition in international law. Most notably, the International Covenant on Social, Economic and Cultural Rights (ICSECR) recognizes the “right of everyone to the enjoyment of the highest attainable standard of physical and mental health” (Art. 12.1). Despite a clear legal obligation on the part of governments to protect, promote, and fulfill this, they often fail to meet the health needs of marginalized groups such as indigenous women, those with mental health problems, and migrants. In this blog post, I will provide an overview of the different accountability mechanisms that exist to hold governments accountable to their right to health obligations, while noting the importance of social accountability mechanisms at the local level. 

Types of Accountability Mechanisms

An accountability mechanism is the “procedure through which government is answerable for its acts or omissions in relation to right to health obligations” (http://repository.essex.ac.uk/9717/1/accountability-right-highest-attainable-standard-health.pdf). Different types of accountability mechanisms exist: judicial (courts); quasi-judicial (human rights institutions); administrative (human rights commission); political (elections); and social (civil society). Each has its strengths and weaknesses. Judicial mechanisms arguably receive the most attention due to high-profile cases where litigants have secured access to life-saving medical treatment through judicial decisions (see e.g. Minister of Health v Treatment Action Campaign). The legal process is undeniably a powerful accountability mechanism in allowing rights-holders to challenge government legislation and policy through the courts. However, marginalized populations often encounter barriers in accessing justice through the courts; the justice system is often too complex, expensive, or culturally insensitive for these groups to navigate.

Social Accountability Mechanisms

Social accountability mechanisms are becoming increasingly important in keeping governments accountable to marginalized people’s right to health and, in my view, deserve greater attention. This type of accountability generally involves the use of citizen action to keep government conduct in check. For instance, the Treatment Action Campaign (TAC) engaged in massive public mobilization and extensive media campaigns to draw attention to the South African government’s restrictions on access to antiretrovirals. 

Social accountability mechanisms at the local level have become more prominent among NGOs seeking to foster citizen participation. On this point, various techniques that allow marginalized populations to assess the performance of government health services have been developed and implemented. CARE Malawi, for example, has developed the “community score card” as a technique for citizens to systematically address local-level barriers to health services and facilitate good governance. The underlying principles of the community score card include participation, inclusion of voice, accountability and transparency, equity, and shared responsibility and obligation. There is evidence that these social accountability mechanisms have a positive effect on health outcomes (https://coregroup.org/wp-content/uploads/media-backup/documents/Resources/Tools/Social_Accountability_Final_online.pdf). 

Conclusion

Human rights, including the right to health, are no more than window-dressing without adequate accountability mechanisms. Accountability provides governments and public officials with the opportunity to explain their actions. Where there are mistakes, accountability demands some form of redress. While human rights actors have traditionally put much effort in using the courts and the electoral process to keep governments accountable, social accountability mechanisms at the local level such as community scorecards deserve attention for their beneficial effects on health outcomes, participation, and empowerment. 

Benny Chan (LLM ’20) is a Global Health Law Scholar at Georgetown University Law Center and a student fellow with the Global Health Initiative.