Key Issues And Questions To Be Considered in Reading Data

¬ Human beings are always behind figures

¬ Figures presented in data are historical - they reflect the epidemic at a specific point in time

C methods used to gather data vary and this can cause confusion
C available data is of differing quality
C individual countries are often (erroneously) treated as homogeneous

¬ Sexual transmission is always recorded as heterosexual (from man to woman or woman to man), bisexual and or homosexual (from man to man).

¬ Do reported figures refer to HIV or to AIDS?

¬ Who are the individuals behind the numbers?

¬ What are their ages?

¬ What work do they do?

¬ What will happen when they stop working: to them, to their families, to their place of work?

¬ What does their illness or HIV status mean to them and their families?

¬ How are they coping?

¬ How is their family, community, working environment, responding to their infection?

¬ Do they have access to care and treatment? What is the quality of services provided or available?

¬ How many are still alive?

¬ How long will they survive, those who are ill?

¬ What will happen to their families when they fall ill or die?

¬ What is the relevance of this information for my programme, my sector, my organization, my own life?

¬ Women are frequently described in data as "housewives", meaning that these women do not work, thus obscuring the unaccounted nature of household work.

¬ What are the impact and costs which would have to be paid to replace unpaid work performed by women?

¬ What role does the mobility of people play in transmission of the virus?

Concepts to Enrich Data Interpretation

Invisibility gender clustering

mobility loss and pain commercial vigour sexual norms

sexual networks social environment wealth and poverty

power and powerlessness dominance and dependency

Pie chart on HIV infection in Occupational Groups

- This kind of data is rarely analysed and infrequently published
- Many of the occupations in this chart are related to mobility
- How might these data have been collected and why?
- What is the proportion of workers in the different job categories in the total population?
- How does the absence of disaggregated information on women affect this presentation?
- How does the absence of complementary data regarding age and income in each occupation affect this presentation?

Map of international road crossing a rural area between Tanzania and Kenya:
the spread of the virus following mobility patterns.

Chart 1: Map of a rural area (p.27)

This is an area with a vigorous local economy. Two of the roads are paved and carry transcontinental traffic; some are all-weather roads, although they may be closed during part of the year. The paths to outlying villages are difficult and only usable on foot or by bicycle.

The people of the area grow food and cash crops. They travel to the towns to sell their surplus and other home-produced products. Some of the village and town people work away from the area in the cities.

The towns on the highways bustle. There are truck stops and bus stops, daily markets. Shops, bars, restaurants, footpath traders and small businesses line the roads. Barbers have set themselves up in the open under the trees. Garages and tire repair shops abound.

People and goods move, openly or illicitly, across the nearby border. The transcontinental highway brings tourists as well as traders, friends, returning villagers and students, government officials, the military and a few other foreigners, often missionaries and consultants. Produce flows out; soap, sugar, cloth, food stuffs, shoes, fertilizers, fuels, tools and much else flow to the town and the villages.

Chart 2: Adult HIV infection rates (1987) (p.28)

Data gathered in 1987 show the virus already widely present. Towns with the greatest commercial vigour are the ones most seriously affected; outlying villages are the least affected. Those infected are often truck drivers, the military, traders or free women.

Adult infection rates in the towns on the highways range from 12% to 20% (in the town at the crossroads).

Chart 3: Adult infection rates (1990) (p.29)

Within 3 years, by 1990, infection rates had increased to a terrifying 50% in the adults in the town at the crossroads and had similarly increased in other towns. By now, even outlying villages are hit. The virus has followed the flow of people, locally and between towns, between villages and towns, as well as into and away from the region.

Poster and radio broadcasts about the virus do not seem to have slowed down its spread, nor has condom availability. Rural isolation has not prevented its entry.

The influences on the spread and extent of spread of the virus would seem to be related to commercial vigour which creates mobility, wealth and power, for example, sexual norms and networks, and the lessening of the cultural and social sanctions and constraints that apply in smaller communities.

Chart 1

Chart 2

Chart 3