Nowadays, epidemiologists are concerned with the correlation between population growth and healthcare issues. The measurement called the “total mid-year population” is most frequently employed instead of the “end-of-year population” because it provides a more comprehensive statistical picture than the latter approach. The correlation with death rates, birth rates, marriage rates, and other indices helps gain a deeper insight into the population changes. Moreover, the end-of-year estimate provides a limited statistical picture of the population changes, affecting data collection and outcome indices.

## Population Measurements

The mid-year measurement is used to determine the number of people at 30^{th} of June annually (Northern Ireland Statistics & Research Agency, 2011, p. 1). This estimate is also called a mean estimate. It is considered to be a way of pinpointing the time at which half of the changes in the population have occurred (Statistical Institute of Jamaica, n.d., par. 1). This measurement is employed to establish the birth rate and the crude birth rate in particular, as well as the death rates and the migration rates during the intercensal period. The arithmetic calculation is also based on averaging between the beginning and the end-year indices (NSO Metadata, n.d., par. 1).

While the mid-year population measurement is an intercensal estimate, the end-of-year measurement is used to determine the number of people in the population as of 31^{st} of December each year. Around the world, various methods are applied. For instance, in the Netherlands, population statistics are published on a monthly basis. France publishes the indices on the 1^{st} of January each year, while Germany conducts both end-year and mid-year measurements (Mort, 2003, p. 71). In the United States, the mid-year measure of population change is employed the most frequently. It is considered to be a more efficient instrument for measuring the population changes per year.

The mid-year population estimate is deemed the most fitting for correlation with the particular period and the statistics on birth rates, death rates, number of marriages, consumption, production, and per capita index (*Appendix A. A note on the “mean population”, *n.d., p. 1). It should be noted that there could be a difference between a mean and mid-year population estimates in countries, where the population is subject to seasonal changes. However, the difference is slight and has little significance (*Appendix A. A note on the “mean population”, *n.d., p. 1). All things considered, the mid-year estimate provides a better representation of the population index for the whole year, as it makes a correlation with an array of essential population changes, including birth rate, death rate, migration, and Medicare statistics (Backus & Mueller, 2012, p. 1). The end-of-year estimate is considered to affect data collection and outcomes of the study.

## Healthcare Issues and Illustrative Examples

Population growth and its influence on the healthcare issues in the country is a major concern for epidemiologists. The overpopulation phenomenon has a negative impact not only on the population’s health but also on the environment (Scutti, 2014, par. 1). In the context of epidemiology, the problem of population growth has become increasingly significant. This phenomenon hinders the efforts of the governments to combat efficiently such diseases as HIV/AIDS or malaria. Moreover, rapid population growth contributes to higher transmission rates of HIV, mother-to-child cases of transmission, unsafe sexual activities, and an increasing number of people engaging in prostitution.

In epidemiology, it is necessary to conduct surveillance over the population’s state of health by means of quantitative or qualitative data. Quantitative data provides a more precise statistical image of the population and baseline indicators. The quantitative indices are easily calculable to determine the incidence and the prevalence of a given disease, as well as morbidity and mortality rates. Thus, the comparison between the end-of-year population estimate and the mid-year population estimate is of utmost importance.

The end-of-year estimate affects data collection and outcomes since, as opposed to the mid-year measurement, it does not provide a correlation with the data obtained at the beginning and the middle of the year. Thus, the statistical picture acquired through the end-of-year estimate is incomplete and insufficiently informative. For instance, in the cases of the abovementioned diseases, i.e. malaria and HIV, the epidemiology incidence rate has to be calculated. However, when using the end-of-year statistics, the obtained results would not provide comprehensive information, as they are limited to the duration of the whole year. Such an approach does not provide a possibility to account for the changes occurring throughout the year when analyzing particular time periods. Thus, the end-of-year population measurement is insufficiently informative and is an obstacle for drawing valid conclusions that could serve as a foundation for development prevention methods and developing other types of preventative health measures.

## Conclusion

In the epidemiological context, the measurement of population changes has a special significance. When comparing the end-of-year and the mid-year population estimates, it is evident that the former constitutes a less efficient method. This approach affects data collection and the obtained outcome data. When faced with a necessity to provide a valid statistical picture of population changes and disease incidence and prevalence, in particular, the end-of-year measurement seems to be an insufficiently comprehensive method.

## References

*Appendix A. A note on the “mean population”.* (n.d.). Web.

Backus, K. & Mueller, L. (2012). *Population statistics for Connecticut*. Web.

Mort, D. (2003). *Understanding statistics and market research data*. London, England: Europa Publications.

Northern Ireland Statistics & Research Agency. (2011). *How are population estimates created? The methodology*. Web.

NSO Metadata. (n.d.). *Mid-year population*. Web.

Scutti, S. (2014). *Overpopulation negatively affects everything from climate change to health care*. Web.

Statistical Institute of Jamaica. (n.d.). *Population and demography*. Web.