October monthly meeting

In our October monthly meeting, James Munday, group member and PhD student at LSHTM, presented his current research on vaccine inequity. Details of his talk are given below.

Why do some sub-populations have higher hospitalisation rates for infectious disease than others and does vaccination impact these inequalities?

There are multiple factors that contribute to inequalities in reported health outcomes between socio-economic, cultural and ethnic sub-groups in the UK. These factors can be defined as:

Dynamic factors: differences which effect the transmission of the infection e.g. social contact behaviours, susceptibility and population structure, and
Static factors: differences in how likely an infected individual is to result in hospitalisation e.g. severity of symptoms, risk factors for complications and reporting biases.

Importantly, the relative influence of dynamic and static factors causing disparities can have a significant impact on the relative behaviour of vaccination in these groups. Due to the herd effects of vaccination groups with lower transmission tend to benefit more from the same level of vaccination than groups with higher transmission potential.

As a result in scenarios where inequalities are caused by dynamic factors, when vaccination is applied but transmission of the infection is not completely interrupted (the critical vaccination threshold), the intervention will most likely increase the inequalities in the burden of disease. In the case where inequalities are present as a result of only static factors, there will be no distributional effect on infection until the critical vaccination threshold is met, when by necessity equality is reached. If these groups are i.e. transmission is also allowed between the groups to some extent, the level of inequality resulting from these dynamic factors is also dependent on the level of integration between the groups, with a higher level of integration (more mixing between populations) resulting in a reduction in the relative increase in inequality.

An understanding of the dynamics of disease inequalities is important when studying the distributional effects of various vaccination programs and concerning assessment of the efficiency-equity trade-off of various interventions.