Fitting a Poisson Regression Model to Reported Deaths from HIV/AIDS in Nigeria

Abstract

Abstract:The Human Immunodeficiency Virus (HIV)/Acquired Immunodeficiency syndrome (AIDS) epidemic has become one of the greatest challenges to public health among adults in Sub-Saharan African. In Nigeria, HIV/AIDS epidemic remain one of the major causes of death in the general population, particularly among young adult. In this paper, we will use Poisson regression model to study the linear trend of annual deaths resulting from HIV/AIDS in Nigeria for the period of 1996 to 2004. The result from the Poisson regression revealed an increase in rate of death resulting from HIV/AIDS in Nigeria. Therefore, there should be increase in the level of awareness of HIV/AIDS and other precautionary measures should also be observed in other to reduce the menace.

Prediction of the COVID-19 Transmission: A Case Study of Pakistan

“…Table 20 shows that the NBR has the smallest AIC and loglikelihood values, as stated by the consequence: (18,985.015, À9,488.507) in males, respectively, while (11,515.044, À6,053.522) in females and is the selected count data model for modelling the suspected, infected and recovered Coronavirus widespread occurrences between males and females in Pakistan. Hence the resulted AIC and log-likelihood shows that males are more prone than females.…”

“…In recent years, a lot of authors used CPM, Poisson regression models (PRMs), and compound Poisson processes (CPP) for various diseases such as a study of the major infection diseases human immunodeficiency virus (HIV) described in sub-Saharan Africa using PRM [ 11 ], to analyse the risk levels of mortality and deadly illness among MERS-CoV patients in the Middle East during 2012 to 2015, Poisson regression with strong variation and a bootstrap-based expectation maximisation model were utilised to cope with significant incomplete information [ 12 ], an interpretation of infinite divisible distribution using Levy–Khintchine Formula with different situations described under the modern interpretations of discrete compound Poisson distributions [ 13 ] and a study on the German Children’s cancer database described using CPP monitoring all children malignancies [ 14 ]. For further understanding related to CPP, PR, NBR, and generalised Poisson regression, refer to the following for more information [ 13 , 15 , 16 ].…”