Analysis of Prevalence of Malaria and Anemia Using Bivariate Probit Model

Senayit Seyoum ()
Additional contact information
Senayit Seyoum: Haramaya University

Annals of Data Science, 2018, vol. 5, issue 2, No 10, 312 pages

Abstract: Abstract Malaria and anemia are public health problems that have an impact on social and economic development. Malaria causes 70,000 deaths each year and accounts for 17% of outpatient visits to health institutions. It is one of the causes of anemia. Therefore, knowing the relation between malaria and anemia could have a great contribution to the development of prevention strategies. This study is intended to jointly model the prevalence of malaria and anemia by employing a bivariate probit model and show their relationship. The data was obtained from 384 patients visiting Alaba health center. The results of the bivariate probit model shows that sex, age, education level and marital status are significantly associated with malaria and sex and education level are significantly associated with anemia. The results of the seemingly unrelated bivariate probit model shows that sex, education level, age and marital status are significantly determining the prevalence of malaria, and malaria, sex and education level are significantly determining the prevalence of anemia.

Keywords: Malaria; Anemia; Bivariate probit; Seemingly unrelated bivariate probit (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s40745-018-0138-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:aodasc:v:5:y:2018:i:2:d:10.1007_s40745-018-0138-3

Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745

DOI: 10.1007/s40745-018-0138-3

Access Statistics for this article

Annals of Data Science is currently edited by Yong Shi

More articles in Annals of Data Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().