Epidemiology Response to Colleagues Post

EPIDEMIOLOGY

Response: Epidemiology

Ola Ola

My colleague in this case opted to focus on childhood obesity. From the onset, he indicates that childhood obesity happens to be one of the most serious health concerns that the country faces at this moment. This is an assertion collaborated by data from the Centers for Disease Control and Prevention – CDC (2022) which makes an observation to the effect that approximately 14.7 million children in America (aged between 2 and 19) happen to be obese – with the prevalence of obesity in this age group estimated to stand at 19.7. This is according to data covering the years 2017-2020. In seeking to explore this particular issue even further, my colleague relies on the various demographic data – with the focus on this front being age, sex, and race/ethnicity. In the healthcare realm, the relevance of demographic data cannot be overstated. Indeed, as Goran (2021) points out, “addressing demographic data allows public health professionals to study health disparities in a population” (110). It therefore follows that the info presented by my colleague on this front can be used to formulate effective context-specific strategies to rein in childhood obesity.

Miles Robinson

My colleague elected to focus on malaria as a crucial public health concern. In addition to describing the areas most affected by this particular disease, my colleague also briefly highlights malaria morbidity and mortality rates. I am of the opinion that to give a more insightful assessment of the issue at hand, my colleague ought to have also highlighted the disease’s fatality rate in the regions highlighted – more specifically in Sub-Saharan Africa, Eastern Mediterranean, as well as Southeast Asia which happen to be the regions most affected by the disease. According to Zeni (2019), the case fatality rate comes in handy in efforts to assess disease fatality. Curley (2020) also makes an observation to the effect that this particular metric could be instrumental in “prognosis (predicting disease course or outcome), where comparatively high rates are indicative of relatively poor outcomes” (198). I am also of the opinion that in addition to geographic factors, my colleague ought to have incorporated additional information on the demographic as well as socio-economic factors linked to this particular disease.