Space-time confounding adjusted determinants of child HIV/TB mortality for large zero-inflated data in rural South Africa

CD4 Trends With Evolving Treatment Initiation Policies Among Children Living With HIV in Zambézia Province, Mozambique, 2012-2018

BACKGROUND

Historically, antiretroviral therapy (ART) initiation was based on CD4 criteria, but this has been replaced with "Test and Start" wherein all people living with HIV are offered ART. We describe the baseline immunologic status among children relative to evolving ART policies in Mozambique.

METHODS

This retrospective evaluation was performed using routinely collected data. Children living with HIV (CL aged 5-14 years) with CD4 data in the period of 2012-2018 were included. ART initiation "policy periods" corresponded to implementation of evolving guidelines: in period 1 (2012-2016), ART was recommended for CD4 <350 cells/mm3; during period 2 (2016-2017), the CD4 threshold increased to <500 cells/mm3; Test and Start was implemented in period 3 (2017-2018). We described temporal trends in the proportion of children with severe immunodeficiency (CD4 <200 cells/mm3) at enrollment and at ART initiation. Multivariable regression models were used to estimate associations with severe immunodeficiency.

RESULTS

The cohort included 1815 children with CD4 data at enrollment and 1922 at ART initiation. The proportion of children with severe immunodeficiency decreased over time: 20% at enrollment into care in period 1 vs. 16% in period 3 (P = 0.113) and 21% at ART initiation in period 1 vs. 15% in period 3 (P = 0.004). Children initiating ART in period 3 had lower odds of severe immunodeficiency at ART initiation compared with those in period 1 [adjusted odds ratio (aOR) = 0.67; 95% CI: 0.51 to 0.88]. Older age was associated with severe immunodeficiency at enrollment (aOR = 1.13; 95% CI: 1.06 to 1.20) and at ART initiation (aOR = 1.14; 95% CI: 1.08 to 1.21).

CONCLUSIONS

The proportion of children with severe immunodeficiency at ART initiation decreased alongside more inclusive ART initiation guidelines. Earlier treatment of children living with HIV is imperative.

A space-time analysis of recurrent malnutrition-related hospitalisations in Kilifi, Kenya for children under-5 years

Background

Globally, malnutrition underlies 45% of under-5 s mortality, mainly from potentiating common infections such as diarrhoea and pneumonia. Malnutrition as a public health problem is not evenly disbursed because of disparities in food insecurity and health, and children commonly suffer recurrent episodes of opportunistic infections. We aimed to understand better the spatial and temporal structure of multiple paediatric hospital admissions associated with malnutrition-related illnesses. This paper aimed to investigate the spatial-temporal variations in malnutrition-related recurrent morbidity of children under-5 years from the Kilifi County in Kenya between 2002 and 2015.

Methods

The study included data from children under-5 years old who had more than one admission to a rural district hospital in Kenya within the Kilifi Health and Demographic Surveillance System (KHDSS). The primary outcome was a malnutrition-related admission, based on wasting (WHZ < -2) or nutritional oedema. Individual, household and environmental level covariates were examined as exposures. We first fitted a SARIMA model for the temporality, and the Moran’s Index affirmed spatial clustering in malnutrition admissions. Kulldorf Statistics using SaTScan were applied to detect hotspots. Then, bivariate analysis was done using repeated values tabulation and analysis of covariance (ANCOVA). Inferential analysis was done using a mixed effect multivariable negative-binomial regression model, adjusting for spatiotemporal random effects.

Results

A total of 2821 children were admitted more than once, giving a total of 6375 admissions. Of these 6375 admissions, 1866 were malnutrition-related, and 3.9% (109/2821) of the children with repeat admissions died. There was a seasonal pattern of re-admissions, peaking from May to July over the years. Hotspots were found in both the Northern and Southern areas of the KHDSS, while the areas near Kilifi Town were least affected. We found that disease severity was most likely associated with a malnutrition re-admission to the hospital.

Conclusion

Disease severity was strongly associated with admission with malnutrition but its effect reduced after adjusting for the spatial and temporal random effects. Adjusting for clustering in space and in time (spatial-temporal) in models helps to improve the understanding of recurrent hospitalisations involving malnutrition.

Electronic supplementary material

The online version of this article (10.1186/s40795-019-0296-5) contains supplementary material, which is available to authorized users.

Geographic Information Systems, spatial analysis, and HIV in Africa: A scoping review

INTRODUCTION

Geographic Information Systems (GIS) and spatial analysis are emerging tools for global health, but it is unclear to what extent they have been applied to HIV research in Africa. To help inform researchers and program implementers, this scoping review documents the range and depth of published HIV-related GIS and spatial analysis research studies conducted in Africa.

METHODS

A systematic literature search for articles related to GIS and spatial analysis was conducted through PubMed, EMBASE, and Web of Science databases. Using pre-specified inclusion criteria, articles were screened and key data were abstracted. Grounded, inductive analysis was conducted to organize studies into meaningful thematic areas.

RESULTS AND DISCUSSION

The search returned 773 unique articles, of which 65 were included in the final review. 15 different countries were represented. Over half of the included studies were published after 2014. Articles were categorized into the following non-mutually exclusive themes: (a) HIV geography, (b) HIV risk factors, and (c) HIV service implementation. Studies demonstrated a broad range of GIS and spatial analysis applications including characterizing geographic distribution of HIV, evaluating risk factors for HIV, and assessing and improving access to HIV care services.

CONCLUSIONS

GIS and spatial analysis have been widely applied to HIV-related research in Africa. The current literature reveals a diversity of themes and methodologies and a relatively young, but rapidly growing, evidence base.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

Risk Assessment and Mapping of Hand, Foot, and Mouth Disease at the County Level in Mainland China Using Spatiotemporal Zero-Inflated Bayesian Hierarchical Models

Hand, foot, and mouth disease (HFMD) is a worldwide infectious disease, prominent in China. China’s HFMD data are sparse with a large number of observed zeros across locations and over time. However, no previous studies have considered such a zero-inflated problem on HFMD’s spatiotemporal risk analysis and mapping, not to mention for the entire Mainland China at county level. Monthly county-level HFMD cases data combined with related climate and socioeconomic variables were collected. We developed four models, including spatiotemporal Poisson, negative binomial, zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models under the Bayesian hierarchical modeling framework to explore disease spatiotemporal patterns. The results showed that the spatiotemporal ZINB model performed best. Both climate and socioeconomic variables were identified as significant risk factors for increasing HFMD incidence. The relative risk (RR) of HFMD at the local scale showed nonlinear temporal trends and was considerably spatially clustered in Mainland China. The first complete county-level spatiotemporal relative risk maps of HFMD were generated by this study. The new findings provide great potential for national county-level HFMD prevention and control, and the improved spatiotemporal zero-inflated model offers new insights for epidemic data with the zero-inflated problem in environmental epidemiology and public health.

How do social-economic differences in urban areas affect tuberculosis mortality in a city in the tri-border region of Brazil, Paraguay and Argentina

Background

The World Health Organization (WHO) launched the “End TB Strategy”, which aims to reduce tuberculosis (TB) mortality by 95% by 2035, Brazil has made a commitment to this, however, one challenge is achieving the goal in the border region, where the TB situation is more critical. The proposal was to analyse the spatial mortality due to TB and its socio-economic determinants in the general population, around the border areas of Brazil, Paraguay and Argentina, as well as the temporal trend in this region.

Method

This ecological study considered the cases of TB deaths of residents of Foz do Iguaçu (BR), with its units of analysis being the census sectors. The standardized mortality rate was calculated for each area. Socioeconomic variables data were obtained from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics (IBGE). The scan statistic was applied to calculate the spatial relative risk (RR), considering a 95% confidence interval (CI). Spatial dependence was analysed using the Global Bivariate Moran I and Local Bivariate Moran I (LISA) to test the relationship between the socioeconomic conditions of the urban areas and mortality from TB. Analysis of the temporal trend was also performed using the Prais-Winsten test.

Results

A total of 74 cases of TB death were identified, of which 53 (71.6%) were male and 51 (68.9%) people of white skin colour. The mortality rate ranged from 0.28 to 22.75 cases per 100,000 inhabitants. A spatial relative risk area was identified, RR = 5.07 (95% CI 1.79–14.30). Mortality was associated with: proportion of people of brown skin colour (I: 0.0440, p = 0.033), income (low income I: − 0.0611, p = 0.002; high income I: − 0.0449, p = 0.026) and density of residents (3 and 4 residents, I: 0.0537, p = 0.007; 10 or more residents, I: − 0.0390, p = 0.035). There was an increase in the mortality rate in people of brown skin colour (6.1%; 95% CI = 0.029, 0.093).

Conclusion

Death due to TB was associated with income, race resident density and social conditions. Although the TB mortality rate is stationary in the general population, it is increasing among people of brown skin colour.

Geo-spatial factors associated with infection risk among young children in rural Ghana: a secondary spatial analysis

Background

Determining the spatial patterns of infection among young children living in a malaria-endemic area may provide a means of locating high-risk populations who could benefit from additional resources for treatment and improved access to healthcare. The objective of this secondary analysis of baseline data from a cluster-randomized trial among 1943 young Ghanaian children (6–35 months of age) was to determine the geo-spatial factors associated with malaria and non-malaria infection status.

Methods

Spatial analyses were conducted using a generalized linear geostatistical model with a Matern spatial correlation function and four definitions of infection status using different combinations of inflammation (C-reactive protein, CRP > 5 mg/L) and malaria parasitaemia (with or without fever). Potentially informative variables were included in a final model through a series of modelling steps, including: individual-level variables (Model 1); household-level variables (Model 2); and, satellite-derived spatial variables (Model 3). A final (Model 4) and maximal model (Model 5) included a set of selected covariates from Models 1 to 3.

Results

The final models indicated that children with inflammation (CRP > 5 mg/L) and/or any evidence of malaria parasitaemia at baseline were more likely to be under 2 years of age, stunted, wasted, live further from a health facility, live at a lower elevation, have less educated mothers, and higher ferritin concentrations (corrected for inflammation) compared to children without inflammation or parasitaemia. Similar results were found when infection was defined as clinical malaria or parasitaemia with/without fever (definitions 3 and 4). Conversely, when infection was defined using CRP only, all covariates were non-significant with the exception of baseline ferritin concentration. In Model 5, all infection definitions that included parasitaemia demonstrated a significant interaction between normalized difference vegetation index and land cover type. Maps of the predicted infection probabilities and spatial random effect showed defined high- and low-risk areas that tended to coincide with elevation and cluster around villages.

Conclusions

The risk of infection among young children in a malaria-endemic area may have a predictable spatial pattern which is associated with geographical characteristics, such as elevation and distance to a health facility.

Original trial registration clinicaltrials.gov (NCT01001871)

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-016-1388-1) contains supplementary material, which is available to authorized users.

Spatial and socio-economic effects on malaria morbidity in children under 5 years in Malawi in 2012

BACKGROUND

Malaria is a major health challenge in sub-Saharan Africa with children under 5 being most vulnerable. Identifying regions of greater malarial burden is vital in targeting interventions.

METHODS

This study analysed malaria morbidity using data from the Malawi 2012 Malaria Indicator Survey that were obtained from Demographic and Health Survey (DHS) program website. These data captured malaria related information on children under 5. Poisson regression was done to determine associations between outcome (number of children under 5 with malaria in household) and explanatory variables. A Bayesian smoothing approach was employed to adjust for spatial random effects on child related variables.

RESULTS

There were 1878 households in 140 clusters. The number of children under five was 1900. Spatially structured effects accounted for more than 90% of random effects as these had a mean of 1.32 (95% Credible Interval (CI)=0.37, 2.50) whilst spatially unstructured had a mean of 0.10 (CI=9.0 × 10(-4), 0.38). Spatially adjusted significant variables were; type of place of residence (urban or rural) [posterior odds ratio (POR)=2.06; CI= 1.27, 3.34], not owning land [POR=1.77; CI=1.19, 2.64], not staying in a slum [POR=0.52; CI=0.33, 0.83] and enhanced vegetation index [POR=0.02; CI=0.00, 1.08]. A trend was observed on usage of insecticide treated mosquito nets [POR=0.80; CI=0.63, 1.03].

CONCLUSION

This study showed that malaria is a disease of poverty. Enhanced vegetation index was an important factor in malaria morbidity. The central region was identified as the area with greatest disease burden.

Determinants of the risk of dying of HIV/AIDS in a rural South African community over the period of the decentralised roll-out of antiretroviral therapy: a longitudinal study

Background

Antiretroviral treatment (ART) has significantly reduced HIV mortality in South Africa. The benefits have not been experienced by all groups. Here we investigate the factors associated with these inequities.

Design

This study was located in a rural South African setting and used data collected from 2007 to 2010, the period when decentralised ART became available. Approximately one-third of the population were of Mozambican origin. There was a pattern of repeated circular migration between urban areas and this community. Survival analysis models were developed to identify demographic, socioeconomic, and spatial risk factors for HIV mortality.

Results

Among the study population of 105,149 individuals, there were 2,890 deaths. The HIV/TB mortality rate decreased by 27% between 2007–2008 and 2009–2010. For other causes of death, the reduction was 10%. Bivariate analysis found that the HIV/TB mortality risk was lower for: those living within 5 km of the Bhubezi Community Health Centre; women; young adults; in-migrants with a longer period of residence; permanent residents; and members of households owning motorised transport, holding higher socioeconomic positions, and with higher levels of education. Multivariate modelling showed, in addition, that those with South Africa as their country of origin had an increased risk of HIV/TB mortality compared to those with Mozambican origins. For males, those of South African origin, and recent in-migrants, the risk of death associated with HIV/TB was significantly greater than that due to other causes.

Conclusions

In this community, a combination of factors was associated with an increased risk of dying of HIV/TB over the period of the roll-out of ART. There is evidence for the presence of barriers to successful treatment for particular sub-groups in the population, which must be addressed if the recent improvements in population-level mortality are to be maintained.

Two decades of mortality change in rural northeast South Africa

BACKGROUND

The MRC/Wits University Agincourt research centre, part of the INDEPTH Network, has documented mortality in a defined population in the rural northeast of South Africa for 20 years (1992-2011) using long-term health and socio-demographic surveillance. Detail on the unfolding, at times unpredicted, mortality pattern has been published. This experience is reviewed here and updated using more recent data.

OBJECTIVE

To present a review and summary of mortality patterns across all age-sex groups in the Agincourt sub-district population for the period 1992-2011 as a comprehensive basis for public health action.

DESIGN

Vital events in the Agincourt population have been updated in annual surveys undertaken since 1992. All deaths have been rigorously recorded and followed by verbal autopsy interviews. Responses to questions from these interviews have been processed retrospectively using the WHO 2012 verbal autopsy standard and the InterVA-4 model for assigning causes of death in a standardised manner.

RESULTS

Between 1992 and 2011, a total of 12,209 deaths were registered over 1,436,195 person-years of follow-up, giving a crude mortality rate of 8.5 per 1,000 person-years. During the 20-year period, the population experienced a major HIV epidemic, which resulted in more than doubling of overall mortality for an extended period. Recent years show signs of declining mortality, but levels remain above the 1992 baseline recorded using the surveillance system.

CONCLUSIONS

The Agincourt population has experienced a major mortality shock over the past two decades from which it will take time to recover. The basic epidemic patterns are consistent with generalised mortality patterns observed in South Africa as a whole, but the detailed individual surveillance behind these analyses allows finer-grained analyses of specific causes, age-related risks, and trends over time. These demonstrate the complex, somewhat unpredicted course of mortality transition over the years since the dawn of South Africa's democratic era in 1994.

Evidence for localised HIV related micro-epidemics associated with the decentralised provision of antiretroviral treatment in rural South Africa: a spatio-temporal analysis of changing mortality patterns (2007-2010)

Background

In this study we analysed the spatial and temporal changes in patterns of mortality over a period when antiretroviral therapy (ART) was rolled out in a rural region of north–eastern South Africa. Previous studies have identified localised concentrated HIV related sub–epidemics and recommended that micro–level analyses be carried out in order to direct focused interventions.

Methods

Data from an ongoing health and socio–demographic surveillance study was used in the analysis. The follow–up was divided into two periods, 2007–2008 and 2009–2010, representing the times immediately before and after the effects on mortality of the decentralised ART provision from a newly established local health centre would be expected to be evident. The study population at the start of the analysis was approximately 73 000 individuals. Data were aggregated by village and also using a 2 × 2 km grid. We identified villages, grid squares and regions in the site where mortality rates within each time period or rate ratios between the periods differed significantly from the overall trends. We used clustering techniques to identify cause–specific mortality hotspots.

Findings

Comparing the two periods, there was a 30% decrease in age and gender standardised adult HIV–related and TB (HIV/TB) mortality with no change in mortality due to other causes. There was considerable spatial heterogeneity in the mortality patterns. Areas separated by 2 to 4 km with very different epidemic trajectories were identified. There was evidence that the impact of ART in reducing HIV/TB mortality was greatest in communities with higher mortality rates in the earlier period.

Conclusions

This study shows the value of conducting high resolution spatial analyses in order to understand how local micro–epidemics contribute to changes seen over a wider area. Such analyses can support targeted interventions.

The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach

BACKGROUND

South Africa accounts for more than a sixth of the global population of people infected with HIV and TB, ranking her highest in HIV/TB co-infection worldwide. Remote areas often bear the greatest burden of morbidity and mortality, yet there are spatial differences within rural settings.

OBJECTIVES

The primary aim was to investigate HIV/TB mortality determinants and their spatial distribution in the rural Agincourt sub-district for children aged 1-5 years in 2004. Our secondary aim was to model how the associated factors were interrelated as either underlying or proximate factors of child mortality using pathway analysis based on a Mosley-Chen conceptual framework.

METHODS

We conducted a secondary data analysis based on cross-sectional data collected in 2004 from the Agincourt sub-district in rural northeast South Africa. Child HIV/TB death was the outcome measure derived from physician assessed verbal autopsy. Modelling used multiple logit regression models with and without spatial household random effects. Structural equation models were used in modelling the complex relationships between multiple exposures and the outcome (child HIV/TB mortality) as relayed on a conceptual framework.

RESULTS

Fifty-four of 6,692 children aged 1-5 years died of HIV/TB, from a total of 5,084 households. Maternal death had the greatest effect on child HIV/TB mortality (adjusted odds ratio=4.00; 95% confidence interval=1.01-15.80). A protective effect was found in households with better socio-economic status and when the child was older. Spatial models disclosed that the areas which experienced the greatest child HIV/TB mortality were those without any health facility.

CONCLUSION

Low socio-economic status and maternal deaths impacted indirectly and directly on child mortality, respectively. These factors are major concerns locally and should be used in formulating interventions to reduce child mortality. Spatial prediction maps can guide policy makers to target interventions where they are most needed.

Estimating the burden of malaria in Senegal: Bayesian zero-inflated binomial geostatistical modeling of the MIS 2008 data

The Research Center for Human Development in Dakar (CRDH) with the technical assistance of ICF Macro and the National Malaria Control Programme (NMCP) conducted in 2008/2009 the Senegal Malaria Indicator Survey (SMIS), the first nationally representative household survey collecting parasitological data and malaria-related indicators. In this paper, we present spatially explicit parasitaemia risk estimates and number of infected children below 5 years. Geostatistical Zero-Inflated Binomial models (ZIB) were developed to take into account the large number of zero-prevalence survey locations (70%) in the data. Bayesian variable selection methods were incorporated within a geostatistical framework in order to choose the best set of environmental and climatic covariates associated with the parasitaemia risk. Model validation confirmed that the ZIB model had a better predictive ability than the standard Binomial analogue. Markov chain Monte Carlo (MCMC) methods were used for inference. Several insecticide treated nets (ITN) coverage indicators were calculated to assess the effectiveness of interventions. After adjusting for climatic and socio-economic factors, the presence of at least one ITN per every two household members and living in urban areas reduced the odds of parasitaemia by 86% and 81% respectively. Posterior estimates of the ORs related to the wealth index show a decreasing trend with the quintiles. Infection odds appear to be increasing with age. The population-adjusted prevalence ranges from 0.12% in Thillé-Boubacar to 13.1% in Dabo. Tambacounda has the highest population-adjusted predicted prevalence (8.08%) whereas the region with the highest estimated number of infected children under the age of 5 years is Kolda (13940). The contemporary map and estimates of malaria burden identify the priority areas for future control interventions and provide baseline information for monitoring and evaluation. Zero-Inflated formulations are more appropriate in modeling sparse geostatistical survey data, expected to arise more frequently as malaria research is focused on elimination.