Poverty and malaria morbidity : a study using count regression model / Paul Kwame Nkegbe, Naasegnibe Kuunibe.

Format:

Book

Author/Creator:

Nkegbe, Paul Kwame, author.

Kuunibe, Naasegnibe, author.

Series:

SAGE Research Methods. Cases.

SAGE Research Methods. Cases

Language:

English

Subjects (All):

Malaria--Epidemiology--Case studies.

Malaria.

Malaria--Economic aspects--Case studies.

Physical Description:

1 online resource.

Place of Publication:

London : SAGE Publications Ltd, 2019.

Summary:

This case study provides a clear example of what to think about in conducting a primary research and the need to clearly measure your variables to reflect your analytical approach as well as context. In particular, we highlight the various count models and explain when to use what. Malaria control programs usually pay little attention to the role socio-economic factors play in disposing households to morbidity due to the disease. This fact is particularly important in low-income settings and especially among poor households. Our earlier research attempted filling this gap. However, this was done from the orientation of applied economics, so in stating the title we made sure that the purpose of the research as well as our analytical approach are highlighted. This is important in carrying the reader along from the beginning on what research problem we are addressing and how we seek to do so. We also identified household socio-economic factors which affect malaria morbidity, not only from the point of view of theory but also from the context in which the study was conducted. The context was particularly important for us to give clear constructs to our variables and ask our questions in such a way to reflect, for example, what would constitute poverty in such a setting, given the term "poverty" is relative. The count regression approach allowed us to establish the link between malaria and poverty.

Notes:

Includes bibliographical references and index.

Description based on XML content.

ISBN:

1-5264-7949-4

9781526479495

OCLC:

1084594138