Divergent Paths of Development: The Modern World-System and Democratization in South Africa and Zambia

This article examines whether a Modern World- Systems (MWS) perspective can provide an improved understanding of the processes of democratization in Africa (and other developing regions of the world) by conducting a comparative case study of South Africa and Zambia in the 1990s, examining the transitions to democracy and divergent processes of democratic consolidation in each country. Semiperipheral South Africa has, due to its more advantageous position in the world-system, been better equipped than peripheral Zambia to safeguard democracy against erosion and reversal. Th e central irony of the MWS is that the weakest states in the MWS can be pushed around by core powers and are more easily forced to democratize while at the same time they are least likely to possess the resources necessary for democratic consolidation. Semiperipheral states can maintain their independence vis-à-vis the core to a higher degree, but if the decision is made to undertake a democratic transition they are more likely to possess the resources necessary for successful consolidation. Th e MWS perspective allows for an improved understanding of the causal pathway of how position in the MWS translates into the ability to consolidate democracy than does approaches that emphasize domestic factors.

Health Awareness Drama by the Mavumbo Youth Group, Mongu Western Zambia, the Trickle Out Project

Video from fieldwork research in Zambia

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

The 1996 ‘Muslim holiday’ affair. Religious competition and state mediation in contemporary Mozambique

Political commentators often cast religious con? ict as the result of the numerical growth and political rise of a single faith. When Islam is involved, arguments about religious fundamentalism are quick to surface and often stand as an explanation in their own right. Yet, as useful as this type of explanation may be, it usually fails to address properly, if at all, two sets of important issues. It avoids, Ž rst, the question of the rise of other religions and their contribution to tensions and con? icts. Second, it reduces the role of the State to a reactive one. The State becomes an object of contest or conquest, or it is simply ignored. Adopting a different approach, this article investigates a controversy that took place in Mozambique in 1996 around the ‘ofŽ cialisation’ of two Islamic holidays. It looks at the role played by religious competition and state mediation. The article shows that the State’s abandonment of religious regulation – the establishment of a free ‘religious market’ – fostered religious competition that created tensions between faiths. It suggests that strife ensued because deregulation was almost absolute: the State did not take a clear stand in religious matters and faith organisations started to believe that the State was becoming, or could become, confessional. The conclusion discusses theoretical implications for the understanding of religious strife as well as Church and State relations. It also draws some implications for the case of Mozambique more speciŽ cally, implications which should have relevance for countries such as Malawi, Zambia and Zimbabwe where problems of a similar nature have arisen.

Search for Rapid Changes in the Visible-Light Corona during the 21 June 2001 Total Solar Eclipse

Some 8000 images obtained with the Solar Eclipse Coronal Imaging System (SECIS) fast-frame CCD camera instrument located at Lusaka, Zambia, during the total eclipse of 21 June 2001 have been analysed to search for short-period oscillations in intensity that could be a signature of solar coronal heating mechanisms by MHD wave dissipation. Images were taken in white-light and Fe xiv green-line (5303 ) channels over 205 seconds (frame rate 39 s(-1)), approximately the length of eclipse totality at this location, with a pixel size of four arcseconds square. The data are of considerably better quality than those that we obtained during the 11 August 1999 total eclipse (Rudawy et al.: Astron. Astrophys. 416, 1179, 2004), in that the images are much better exposed and enhancements in the drive system of the heliostat used gave a much improved image stability. Classical Fourier and wavelet techniques have been used to analyse the emission at 29 518 locations, of which 10 714 had emission at reasonably high levels, searching for periodic fluctuations with periods in the range 0.1 -aEuro parts per thousand 17 seconds (frequencies 0.06 -aEuro parts per thousand 10 Hz). While a number of possible periodicities were apparent in the wavelet analysis, none of the spatially and time-limited periodicities in the local brightness curves was found to be physically important. This implies that the pervasive Alfv,n wave-like phenomena (Tomczyk et al.: Science 317, 1192, 2007) using polarimetric observations with the Coronal Multi-Channel Polarimeter (CoMP) instrument do not give rise to significant oscillatory intensity fluctuations.

Trickle Out Africa website

Includes free business directory of 4000 social and environmental enterprises across 19 countries of Eastern and Southern Africa. Also profiles over 20 cases studies across Zambia, Kenya, South Africa and Mozambique.

Using interviewer random effects to remove selection bias from HIV prevalence estimates

Background: Selection bias in HIV prevalence estimates occurs if non-participation in testing is correlated with HIV status. Longitudinal data suggests that individuals who know or suspect they are HIV positive are less likely to participate in testing in HIV surveys, in which case methods to correct for missing data which are based on imputation and observed characteristics will produce biased results. Methods: The identity of the HIV survey interviewer is typically associated with HIV testing participation, but is unlikely to be correlated with HIV status. Interviewer identity can thus be used as a selection variable allowing estimation of Heckman-type selection models. These models produce asymptotically unbiased HIV prevalence estimates, even when non-participation is correlated with unobserved characteristics, such as knowledge of HIV status. We introduce a new random effects method to these selection models which overcomes non-convergence caused by collinearity, small sample bias, and incorrect inference in existing approaches. Our method is easy to implement in standard statistical software, and allows the construction of bootstrapped standard errors which adjust for the fact that the relationship between testing and HIV status is uncertain and needs to be estimated. Results: Using nationally representative data from the Demographic and Health Surveys, we illustrate our approach with new point estimates and confidence intervals (CI) for HIV prevalence among men in Ghana (2003) and Zambia (2007). In Ghana, we find little evidence of selection bias as our selection model gives an HIV prevalence estimate of 1.4% (95% CI 1.2% – 1.6%), compared to 1.6% among those with a valid HIV test. In Zambia, our selection model gives an HIV prevalence estimate of 16.3% (95% CI 11.0% - 18.4%), compared to 12.1% among those with a valid HIV test. Therefore, those who decline to test in Zambia are found to be more likely to be HIV positive. Conclusions: Our approach corrects for selection bias in HIV prevalence estimates, is possible to implement even when HIV prevalence or non-participation is very high or very low, and provides a practical solution to account for both sampling and parameter uncertainty in the estimation of confidence intervals. The wide confidence intervals estimated in an example with high HIV prevalence indicate that it is difficult to correct statistically for the bias that may occur when a large proportion of people refuse to test.

On the Assumption of Bivariate Normality in Selection Models: A Copula Approach Applied to Estimating HIV Prevalence

Background: Heckman-type selection models have been used to control HIV prevalence estimates for selection bias when participation in HIV testing and HIV status are associated after controlling for observed variables. These models typically rely on the strong assumption that the error terms in the participation and the outcome equations that comprise the model are distributed as bivariate normal.
Methods: We introduce a novel approach for relaxing the bivariate normality assumption in selection models using copula functions. We apply this method to estimating HIV prevalence and new confidence intervals (CI) in the 2007 Zambia Demographic and Health Survey (DHS) by using interviewer identity as the selection variable that predicts participation (consent to test) but not the outcome (HIV status).
Results: We show in a simulation study that selection models can generate biased results when the bivariate normality assumption is violated. In the 2007 Zambia DHS, HIV prevalence estimates are similar irrespective of the structure of the association assumed between participation and outcome. For men, we estimate a population HIV prevalence of 21% (95% CI = 16%–25%) compared with 12% (11%–13%) among those who consented to be tested; for women, the corresponding figures are 19% (13%–24%) and 16% (15%–17%).
Conclusions: Copula approaches to Heckman-type selection models are a useful addition to the methodological toolkit of HIV epidemiology and of epidemiology in general. We develop the use of this approach to systematically evaluate the robustness of HIV prevalence estimates based on selection models, both empirically and in a simulation study.

A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses

Estimates of HIV prevalence are important for policy in order to establish the health status of a country's population and to evaluate the effectiveness of population-based interventions and campaigns. However, participation rates in testing for surveillance conducted as part of household surveys, on which many of these estimates are based, can be low. HIV positive individuals may be less likely to participate because they fear disclosure, in which case estimates obtained using conventional approaches to deal with missing data, such as imputation-based methods, will be biased. We develop a Heckman-type simultaneous equation approach which accounts for non-ignorable selection, but unlike previous implementations, allows for spatial dependence and does not impose a homogeneous selection process on all respondents. In addition, our framework addresses the issue of separation, where for instance some factors are severely unbalanced and highly predictive of the response, which would ordinarily prevent model convergence. Estimation is carried out within a penalized likelihood framework where smoothing is achieved using a parametrization of the smoothing criterion which makes estimation more stable and efficient. We provide the software for straightforward implementation of the proposed approach, and apply our methodology to estimating national and sub-national HIV prevalence in Swaziland, Zimbabwe and Zambia.