**6.1 Population of study**

254 Social and Psychological Aspects of HIV/AIDS and Their Ramifications

HIV/AIDS retards economic growth by destroying human capital. According to a UN report, HIV/AIDS epidemics will have devastating consequences in decades to come for virtually every sector of society ranging from households, farms and other economic activities (Nomcebo, 2005). The epidemic is predicted to hinder possibility of achieving UN millennium development goals within most affected regions, particularly sub Saharan

Agriculture is one of the most important sectors in several developing countries, particularly when measured by the percentage of people dependent on it for their livelihood. Although the sector may produce only 20% of a country's wealth (measured as a percentage of the gross national product), it might provide a living (survival) for as much as 80% of some developing countries' populations (Agarwal, 2002). Indirectly, it provides a living for other parts of the population, for example, processing workers on sugar estates. The effect of AIDS is debilitating at a family level. As an infected farmer becomes increasingly ill, he and family members who take care of him, spend less and less time working on family crops. The family, therefore, begins to lose income from "un-marketed" or incompletely tended crops, and may even sell off farm implements or household

This cycle is compounded by high costs of health care. Whether the sick person turns to a traditional healer or to health services, he/she will surely spend money. A 1997 study by the Food and Agriculture Organization of the United Nations (FAO) showed that in the midwest of Cote d' ivories (Ivory Coast), care for male AIDS patients cost, on average, about US\$ 300 a year, which is a quarter to a half of the net annual income for most small scale farms (Kaplan, 2000). The time lost by family members should also be taken into account. For instance, repeated absence of another member of the farm to accompany the patient to a healer, also reduces the farm's production. Also, when the most debilitating phases of AIDS coincide with key farming periods such as clearing or sowing, time spent nursing a sick

Some companies in Africa have already felt the impact of HIV on their bottom line. A manager at one sugar processing estate in Kenya counted the cost of HIV infection in a number of ways: absenteeism (8000 days of labour cost owing to sickness between 1995 and 1997 alone); lower productivity (50% drop in the ratio of processed sugar recovered from raw care between 1993 and 1997) and higher overtime costs for workers who are obliged to

The research methodology encompasses different techniques and procedures that are used to collect and analyze data for research. This is important, since it provides a better view of how the conclusion was made. The methodology covers the population of study, method of

work longer hours to compensate for the void left by sick colleagues (Booth, 2005).

member, certainly has a negative impact on turnover (Answers.com, 2009).

**5.1 Economic impact** 

Africa (Todaro, 1992).

**5.3 HIV and business** 

**6. Research methodology** 

data collection and data analysis technique.

**5.2 Impact on agriculture** 

properties as a means to survive (Dhar, 1999).

The population of study comprises countries that have the highest prevalence of HIV/AIDS epidemic in sub-Saharan Africa. These countries are Botswana, Kenya, Uganda, South Africa and Zimbabwe, and were used to reflect rising trends of the epidemic.

#### **6.2 Method of data collection and analysis**

Data for the research was obtained from secondary sources such as textbooks, journal articles and the internet. The data collected was analyzed by use of the T-test, which is used when comparing two population means. The formula for finding significant differences between two independent means is stated as follows:

$$\begin{aligned} \mathbf{t} &= \overline{\mathbf{x}\_1} - \overline{\mathbf{x}\_2} \\ & \left(\mathbf{N} \mathbf{s}\_1^2 + \mathbf{N}\_2 \mathbf{S}\_2^2\right) \mathbf{(N}\_1 + \mathbf{N}\_2) \\ & \sqrt{\left(\mathbf{N}\_1 + \mathbf{N}\_2 - 2\right)} \left(\mathbf{N}\_1 \mathbf{N}\_2\right) \end{aligned}$$

Where 1 x = mean of the first group

<sup>2</sup> x = means of the second group

N1 = number of cases in the first group

N2 =number of cases in the second group

S1 =standard deviation of the first group

S2 =standard deviation of the second group

In using this formula, the degree of freedom (d.f) is noted.

At the end, if the value of the critical value is less than the calculated value, the null hypothesis is rejected and the alternative hypothesis is accepted.
