A systems dynamic model for drug abuse and drug-related crime in the Western Cape Province of South Africa

CITATION: Nyabadza, F. & Coetzee, L. 2017. A systems dynamic model for drug abuse and drug-related crime in the Western Cape Province of South Africa. Computational and Mathematical Methods in Medicine, 2017:1-14 (Article ID 4074197), doi:10.1155/2017/4074197.The original publication is available at http://www.hindawi.com/journals/cmmmPublication of this article was funded by the Stellenbosch University Open Access Fund.The complex problem of drug abuse and drug-related crimes in communities in the Western Cape province cannot be studied in isolation but through the system they are embedded in. In this paper, a theoretical model to evaluate the syndemic of substance abuse and drug-related crimes within the Western Cape province of South Africa is constructed and explored. The dynamics of drug abuse and drug-related crimes within the Western Cape are simulated using STELLA software. The simulation results are consistent with the data from SACENDU and CrimeStats SA, highlighting the usefulness of such a model in designing and planning interventions to combat substance abuse and its related problems.https://www.hindawi.com/journals/cmmm/2017/4074197/abs/Publisher's versio

Modelling Drug Abuse and Drug-related Crime: A Systems Approach

Thesis (MSc)--Stellenbosch University, 2015ENGLISH ABSTRACT : In this study we look at the syndemic of substance abuse and drug-related crime in the Western Cape province of South Africa. The intent of this study is to provoke critical thinking about the possibilities systems thinking and system dynamics posses for social and health challenges in a diverse and complex environment like that of South Africa, especially the Western Cape. This study ventures into cross-discipline work between Epidemiology, Biomathematics and System Dynamics, with the hope of encouraging researchers from different fields to collaborate in order to curb the scourge of substance abuse and drug-related crime in South Africa. Substance abuse and the associated health and social hazards such as drug-related crime is a major problem in the Western Cape. Drug-related crime cases reported by the South African Police Services (SAPS) for the Western Cape exhibited a 311.5% growth in the past decade. This highlights how the reduction of substance abuse and drug-related crime within theWestern Cape province, will be an elixir for the safety and development of the communities. The fight against substance abuse has been driven by a multi-sectorial approach involving several government departments, non-governmental organisations and communities. With systems thinking the assumption is that the world is systemic, which means that phenomena is understood to be an emergent property of the interrelated whole. Firstly, using non-linear ordinary differential equations, we formulate a deterministic mathematical model for the substance abuse and drug-related crime syndemic, evaluate the threshold number and use sensitivity analysis to analyze the model. Secondly, a dynamic system, called the Substance Abuse and Drug-related Crime in theWestern Cape (SADC-WC) system is constructed using the STELLA in order to explore and classify the underlying relationships and structures within the substance abuse and drug-related crime system. Both the sensitivity analysis, and the simulations of the SADC-WC system indicate that an increase of successful convictions will have a significant influence on the syndemic, and promise to reduce drug-related crime cases.AFRIKAANSE OPSOMMING : In hierdie studie ondersoek on die syndemie (‘syndemic’) van dwelmmisbruik en dwelmverwante misdaad in die Wes-Kaap provinsie, in Suid-Afrika. Die moontlikhede wat sistemiese denke en dinamiese sisteme inhou vir sosiale en gesondheid kwale in ’n diverse en komplekse omgewing soos Suid-Afrika, word ondersoek. Hierdie studie waag interdisiplinêre werk tussen Epidemiologie, Biowiskunde en Dinamiese sisteme, met die hoop om navorsers van verskillende velde aan te moedig om saam te werk om die plaag van dwelmmisbruik en dwelm-verwante misdaad in Suid-Afrika te bekamp. Dwelmmisbruik en die gepaardgaande gesondheid en maatskaplike gevare soos dwelmverwante misdaad is ’n groot probleem in dieWes-Kaap. Die SAPD se vermelde dwelmverwante midaad het ’n groei van 311,5% ondergaan in die afgelope dekade, en is aanduidend vir hoe die beheer en beperking van dwelmmisbruik en dwelm-verwante misdaad in die Wes-Kaap provinsie bevordering van beide die veiligheid en ontwikkeling van die gemeenskap sal verseker. Dit beklemtoon hoe die vermindering van dwelmmisbruik en dwelm-verwante misdaad in dieWes-Kaapland, sal ’n elikser vir die veiligheid en ontwikkeling van die gemeenskappe. Die stryd teen dwelmmisbruik is gedryf deur ’n multi-sektorale benadering waarby verskeie regeringsdepartemente, nie-regerings organisasies en gemeenskappe. Stelsels denke en dinamiese sisteme is gebasseur op die aanname, dat die wÃłreld is sistemiese en dat verskynsels verstaan word ten opsigte van die ontluikende eienskap van die omvattende geheel. Eerstens stel ons ’n kompartementele model op wat deur nie-liniêre gewone differensiële vergelykings beskryf kan word vir die dwelmmisbruik en dwelm-verwante misdaad epidemies. Ons evalueer die drumpel getal en gebruik sensitiwiteitsanalise om die parameters van die model te analiseer. Tweedens, is ’n dinamiese sisteem genaamd die Middelmisbruik en dwelmverwante misdaad in dieWes-Kaap (SADC-WC) stelsel gebou met behulp van die STELLA platform om te verken en klassifiseer die onderliggende verhoudings en strukture binne die dwelmmisbruik en dwelm-verwante misdaad stelsel. Beide die sensitiwiteitsanalise, en die simulasies van die SADC-WC stelsel dui aan dat ’n toename in suksesvolle vonisse ’n beduidende invloed op die epidemies sal hê; en beloof om sake van dwelmverwante misdaad te verminder

Evaluation of a community health worker home visit intervention to improve child development in South Africa: A cluster-randomized controlled trial.

BackgroundEffective integration of home visit interventions focused on early childhood development into existing service platforms is important for expanding access in low- and middle-income countries (LMICs). We designed and evaluated a home visit intervention integrated into community health worker (CHW) operations in South Africa.Methods and findingsWe conducted a cluster-randomized controlled trial in Limpopo Province, South Africa. CHWs operating in ward-based outreach teams (WBOTs; clusters) and caregiver-child dyads they served were randomized to the intervention or control group. Group assignment was masked from all data collectors. Dyads were eligible if they resided within a participating CHW catchment area, the caregiver was at least 18 years old, and the child was born after December 15, 2017. Intervention CHWs were trained on a job aid that included content on child health, nutrition, developmental milestones, and encouragement to engage in developmentally appropriate play-based activities, for use during regular monthly home visits with caregivers of children under 2 years of age. Control CHWs provided the local standard of care. Household surveys were administered to the full study sample at baseline and endline. Data were collected on household demographics and assets; caregiver engagement; and child diet, anthropometry, and development scores. In a subsample of children, electroencephalography (EEG) and eye-tracking measures of neural function were assessed at a lab concurrent with endline and at 2 interim time points. Primary outcomes were as follows: height-for-age z-scores (HAZs) and stunting; child development scores measured using the Malawi Developmental Assessment Tool (MDAT); EEG absolute gamma and total power; relative EEG gamma power; and saccadic reaction time (SRT)-an eye-tracking measure of visual processing speed. In the main analysis, unadjusted and adjusted impacts were estimated using intention-to-treat analysis. Adjusted models included a set of demographic covariates measured at baseline. On September 1, 2017, we randomly assigned 51 clusters to intervention (26 clusters, 607 caregiver-child dyads) or control (25 clusters, 488 caregiver-child dyads). At endline (last assessment June 11, 2021), 432 dyads (71%) in 26 clusters remained in the intervention group, and 332 dyads (68%) in 25 clusters remained in the control group. In total, 316 dyads attended the first lab visit, 316 dyads the second lab visit, and 284 dyads the third lab visit. In adjusted models, the intervention had no significant impact on HAZ (adjusted mean difference (aMD) 0.11 [95% confidence interval (CI): -0.07, 0.30]; p = 0.220) or stunting (adjusted odds ratio (aOR) 0.63 [0.32, 1.25]; p = 0.184), nor did the intervention significantly impact gross motor skills (aMD 0.04 [-0.15, 0.24]; p = 0.656), fine motor skills (aMD -0.04 [-0.19, 0.11]; p = 0.610), language skills (aMD -0.02 [-0.18, 0.14]; p = 0.820), or social-emotional skills (aMD -0.02 [-0.20, 0.16]; p = 0.816). In the lab subsample, the intervention had a significant impact on SRT (aMD -7.13 [-12.69, -1.58]; p = 0.012), absolute EEG gamma power (aMD -0.14 [-0.24, -0.04]; p = 0.005), and total EEG power (aMD -0.15 [-0.23, -0.08]; p ConclusionsWhile the home visit intervention did not significantly impact linear growth or skills, we found significant improvement in SRT. This study contributes to a growing literature documenting the positive effects of home visit interventions on child development in LMICs. This study also demonstrates the feasibility of collecting markers of neural function like EEG power and SRT in low-resource settings.Trial registrationPACTR 201710002683810; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=2683; South African Clinical Trials Registry, SANCTR 4407

Sample description as proportion of target.

Sample description as proportion of target.</p

GW-2012 2018 NDoH treatment record.

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Site of disease details.

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2x2 Tables comparing lab results.

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Accuracy of demographic information, by source of information (n = 277).

Accuracy of demographic information, by source of information (n = 277).</p

Completeness of data between clinic records and TIER.Net for key TB-related variables (n = 222).

Completeness of data between clinic records and TIER.Net for key TB-related variables (n = 222).</p

Measures of agreement between categorical variables captured in the clinic record and TIER.Net (n = 222).

Measures of agreement between categorical variables captured in the clinic record and TIER.Net (n = 222).</p