Seroprevalence of Toxoplasma gondii infection among pregnant women in Windhoek, Namibia, in 2016

Background

When a pregnant woman contracts Toxoplasma gondii (T. gondii) infection during pregnancy, it may be vertically transmitted to the foetus. Information on the incidence of congenital toxoplasmosis (CT) in developing countries is scarce. Most studies focus on the seroprevalence of T. gondii infection among pregnant women. This study aimed to determine the seroprevalence of T. gondii infection among pregnant women attending public antenatal care in Windhoek, Namibia, in 2016.

Methods

In this descriptive study, 344 urban pregnant women attending public antenatal care were voluntarily enrolled in the study. Seroprevalence of anti-T. gondii Immunoglobulin G (IgG) was determined by automated immunoassay. Samples with a positive T. gondii IgG result were tested for T. gondii Immunoglobulin M (IgM) and specific IgG avidity by using an enzyme-linked immunosorbent assay (ELISA) test. A questionnaire captured demographic data and exposure to risk factors. Data were analysed using Statistical Package for the Social Sciences (SPSS) and R.

Results

Anti-T. gondii IgG was found in nine (2.61%) pregnant women. There was no association of anti-T. gondii IgG with demographic characteristics or exposure to risk factors.Anti-T. gondii IgM was positive in one (0.3%) woman, while three (0.9%) women had borderline anti-T. gondii IgM results. Specific IgG avidity was low, equivocal and high in 0%, 33% and 67% of seropositive pregnant women, respectively.

Conclusion

Seroprevalence of anti-T. gondii IgG is much lower in Namibia than is reported in other developing countries. Investigation into specific IgM seropositivity and IgG avidity showed that pregnant women in the central region of Namibia are at low risk of vertical transmission and development of CT.

Joint spatial modelling of disease risk using multiple sources: an application on HIV prevalence from antenatal sentinel and demographic and health surveys in Namibia

Background

In disease mapping field, researchers often encounter data from multiple sources. Such data are fraught with challenges such as lack of a representative sample, often incomplete and most of which may have measurement errors, and may be spatially and temporally misaligned. This paper presents a joint model in the effort to deal with the sampling bias and misalignment.

Methods

A joint (bivariate) spatial model was applied to estimate HIV prevalence using two sources: 2014 National HIV Sentinel survey (NHSS) among pregnant women aged 15–49 years attending antenatal care (ANC) and the 2013 Namibia Demographic and Health Surveys (NDHS).

Results

Findings revealed that health districts and constituencies in the northern part of Namibia were found to be highly associated with HIV infection. Also, the study showed that place of residence, gender, gravida, marital status, number of kids dead, wealth index, education, and condom use were significantly associated with HIV infection in Namibia.

Conclusion

This study had shown determinants of HIV infection in Namibia and had revealed areas at high risk through HIV prevalence mapping. Moreover, a joint modelling approach was used in order to deal with spatially misaligned data. Finally, it was shown that prediction of HIV prevalence using the NDHS data source can be enhanced by jointly modelling other HIV data such as NHSS data. These findings would help Namibia to tailor national intervention strategies for specific regions and groups of population.