Journal Article > ResearchFull Text
BMJ Glob Health. 1 December 2022; Volume 7 (Issue 12); e009674.; DOI:10.1136/bmjgh-2022-009674
Van Bortel W, Mariën J, Jacobs BKM, Sinzinkayo D, Sinarinzi P, et al.
BMJ Glob Health. 1 December 2022; Volume 7 (Issue 12); e009674.; DOI:10.1136/bmjgh-2022-009674
BACKGROUND
Long-lasting insecticidal nets (LLINs) are one of the key interventions in the global fight against malaria. Since 2014, mass distribution campaigns of LLINs aim for universal access by all citizens of Burundi. In this context, we assess the impact of LLINs mass distribution campaigns on malaria incidence, focusing on the endemic highland health districts. We also explored the possible correlation between observed trends in malaria incidence with any variations in climate conditions.
METHODS
Malaria cases for 2011—2019 were obtained from the National Health Information System. We developed a generalised additive model based on a time series of routinely collected data with malaria incidence as the response variable and timing of LLIN distribution as an explanatory variable to investigate the duration and magnitude of the LLIN effect on malaria incidence. We added a seasonal and continuous-time component as further explanatory variables, and health district as a random effect to account for random natural variation in malaria cases between districts.
RESULTS
Malaria transmission in Burundian highlands was clearly seasonal and increased non-linearly over the study period. Further, a fast and steep decline of malaria incidence was noted during the first year after mass LLIN distribution (p<0.0001). In years 2 and 3 after distribution, malaria cases started to rise again to levels higher than before the control intervention.
CONCLUSION
This study highlights that LLINs did reduce the incidence in the first year after a mass distribution campaign, but in the context of Burundi, LLINs lost their impact after only 1 year.
Long-lasting insecticidal nets (LLINs) are one of the key interventions in the global fight against malaria. Since 2014, mass distribution campaigns of LLINs aim for universal access by all citizens of Burundi. In this context, we assess the impact of LLINs mass distribution campaigns on malaria incidence, focusing on the endemic highland health districts. We also explored the possible correlation between observed trends in malaria incidence with any variations in climate conditions.
METHODS
Malaria cases for 2011—2019 were obtained from the National Health Information System. We developed a generalised additive model based on a time series of routinely collected data with malaria incidence as the response variable and timing of LLIN distribution as an explanatory variable to investigate the duration and magnitude of the LLIN effect on malaria incidence. We added a seasonal and continuous-time component as further explanatory variables, and health district as a random effect to account for random natural variation in malaria cases between districts.
RESULTS
Malaria transmission in Burundian highlands was clearly seasonal and increased non-linearly over the study period. Further, a fast and steep decline of malaria incidence was noted during the first year after mass LLIN distribution (p<0.0001). In years 2 and 3 after distribution, malaria cases started to rise again to levels higher than before the control intervention.
CONCLUSION
This study highlights that LLINs did reduce the incidence in the first year after a mass distribution campaign, but in the context of Burundi, LLINs lost their impact after only 1 year.
Journal Article > ResearchFull Text
PLOS One. 29 July 2022; Volume 17 (Issue 7); e0271910.; DOI:10.1371/journal.pone.0271910
Mesic A, Decroo T, Mar HT, Jacobs BKM, Thandar MP, et al.
PLOS One. 29 July 2022; Volume 17 (Issue 7); e0271910.; DOI:10.1371/journal.pone.0271910
INTRODUCTION
Despite HIV viral load (VL) monitoring being serial, most studies use a cross-sectional design to evaluate the virological status of a cohort. The objective of our study was to use a simplified approach to calculate viraemic-time: the proportion of follow-up time with unsuppressed VL above the limit of detection. We estimated risk factors for higher viraemic-time and whether viraemic-time predicted mortality in a second-line antiretroviral treatment (ART) cohort in Myanmar.
METHODS
We conducted a retrospective cohort analysis of people living with HIV (PLHIV) who received second-line ART for a period >6 months and who had at least two HIV VL test results between 01 January 2014 and 30 April 2018. Fractional logistic regression assessed risk factors for having higher viraemic-time and Cox proportional hazards regression assessed the association between viraemic-time and mortality. Kaplan-Meier curves were plotted to illustrate survival probability for different viraemic-time categories.
RESULTS
Among 1,352 participants, 815 (60.3%) never experienced viraemia, and 172 (12.7%), 214 (15.8%), and 80 (5.9%) participants were viraemic <20%, 20–49%, and 50–79% of their total follow-up time, respectively. Few (71; 5.3%) participants were ≥80% of their total follow-up time viraemic. The odds for having higher viraemic-time were higher among people with a history of injecting drug use (aOR 2.01, 95% CI 1.30–3.10, p = 0.002), sex workers (aOR 2.10, 95% CI 1.11–4.00, p = 0.02) and patients treated with lopinavir/ritonavir (vs. atazanavir; aOR 1.53, 95% CI 1.12–2.10, p = 0.008). Viraemic-time was strongly associated with mortality hazard among those with 50–79% and ≥80% viraemic-time (aHR 2.92, 95% CI 1.21–7.10, p = 0.02 and aHR 2.71, 95% CI 1.22–6.01, p = 0.01). This association was not observed in those with viraemic-time <50%.
CONCLUSIONS
Key populations were at risk for having a higher viraemic-time on second-line ART. Viraemic-time predicts clinical outcomes. Differentiated services should target subgroups at risk for a higher viraemic-time to control both HIV transmission and mortality.
Despite HIV viral load (VL) monitoring being serial, most studies use a cross-sectional design to evaluate the virological status of a cohort. The objective of our study was to use a simplified approach to calculate viraemic-time: the proportion of follow-up time with unsuppressed VL above the limit of detection. We estimated risk factors for higher viraemic-time and whether viraemic-time predicted mortality in a second-line antiretroviral treatment (ART) cohort in Myanmar.
METHODS
We conducted a retrospective cohort analysis of people living with HIV (PLHIV) who received second-line ART for a period >6 months and who had at least two HIV VL test results between 01 January 2014 and 30 April 2018. Fractional logistic regression assessed risk factors for having higher viraemic-time and Cox proportional hazards regression assessed the association between viraemic-time and mortality. Kaplan-Meier curves were plotted to illustrate survival probability for different viraemic-time categories.
RESULTS
Among 1,352 participants, 815 (60.3%) never experienced viraemia, and 172 (12.7%), 214 (15.8%), and 80 (5.9%) participants were viraemic <20%, 20–49%, and 50–79% of their total follow-up time, respectively. Few (71; 5.3%) participants were ≥80% of their total follow-up time viraemic. The odds for having higher viraemic-time were higher among people with a history of injecting drug use (aOR 2.01, 95% CI 1.30–3.10, p = 0.002), sex workers (aOR 2.10, 95% CI 1.11–4.00, p = 0.02) and patients treated with lopinavir/ritonavir (vs. atazanavir; aOR 1.53, 95% CI 1.12–2.10, p = 0.008). Viraemic-time was strongly associated with mortality hazard among those with 50–79% and ≥80% viraemic-time (aHR 2.92, 95% CI 1.21–7.10, p = 0.02 and aHR 2.71, 95% CI 1.22–6.01, p = 0.01). This association was not observed in those with viraemic-time <50%.
CONCLUSIONS
Key populations were at risk for having a higher viraemic-time on second-line ART. Viraemic-time predicts clinical outcomes. Differentiated services should target subgroups at risk for a higher viraemic-time to control both HIV transmission and mortality.
Conference Material > Slide Presentation
Leclair C, Marien J, Sinzinkayo D, Abdelrahman A, Lampaert E, et al.
MSF Scientific Days International 2021: Research. 19 May 2021
Conference Material > Abstract
Leclair C, Marien J, Sinzinkayo D, Abdelrahman A, Lampaert E, et al.
MSF Scientific Days International 2021: Research. 19 May 2021
INTRODUCTION
In Burundi, malaria continues to be a major public health issue as the leading cause of health facility attendance, high levels of mortality and devastating malaria epidemics in highland areas. Since 2004, Burundi’s National Malaria Control Programme (PNILP) has developed an integrated malaria control strategy. Since 2016, Médecins Sans Frontières (MSF), in collaboration with the PNILP, has implemented integrated malaria control interventions within two malaria endemic health districts located in the central highlands and eastern border regions.
METHODS
We re-assessed epidemiological trends for malaria in Burundi to: (1) evaluate spatial heterogeneity and seasonality; (2) longitudinally describe trends in disease incidence for three epidemiological strata; and (3) assess the association between long-lasting insecticidal net (LLIN) mass distribution campaigns (MDC) and disease incidence. Analysis used malaria case data, routinely collected and reported weekly by PNILP from 2011- 2019. Malaria cases were converted into incidence rates, using existing population data, and expressed per 1000 population at risk. Health districts (n=47) were categorized into three different strata based upon geographic elevation and endemic channels, using the quartile method. A generalized additive mixed model (GAMM) was implemented in R to analyze time-series data.
ETHICS
This work met the requirements for exemption from MSF Ethics Review Board review, and was conducted with permission from Sebastian Spencer, Medical Director, Operational Centre Brussels, MSF.
RESULTS
From 2011-2016, seasonality and intensity of malaria transmission was heterogeneous across the three epidemiological strata. The median incidence (cases/1000 population) for health districts <1200m elevation was 6.0 (interquartile range, IQR, 4.3-8.5); for those 1200-1850m, incidence was 12.3 (IQR 8.0-17.6); and for those >1850m, incidence was 2.1 (IQR 1.1-6.3). In contrast to the observed incidence rates for health districts within the endemic channels at <1200m and >1850m, health districts within the endemic
channel at 1200-1850m showed marked seasonality, with a bimodal distribution. Health districts in these endemic channels, had peaks in median incidence of 17.6 cases/1000 and 15.1cases/1000 population in weeks 26 and 52, respectively. GAMM analysis suggested an increasing trend in malaria incidence over the period 2011—2019. The analysis further revealed that LLIN-MDC campaigns were associated with a rapid reduction in malaria incidence, but the epidemiological impact was attenuated after one year. Specifically, comparing malaria incidence in three health districts adjacent to MSF’s intervention area (1200-1850m channel), the 2017 LLIN-MCD was associated with a 44% reduction in clinical incidence one year post-distribution (RR 0.56, 95%CI 0.556-0.56), but no evidence for a reduction two years post-distribution was observed RR 1.10 (95%CI 1.092-1.099).
CONCLUSION
These findings highlight the effectiveness of LLIN as a malaria control intervention across different epidemiological strata in Burundi. However, the duration of functional effectiveness of LLIN is most definitely less than 3 years and may be shorter than one year in Burundi. The reasons underlying these finding are legion. Further operational research is needed to disentangle the dynamic interplay between operational, human behavioural, sociological, and entomological factors.
In Burundi, malaria continues to be a major public health issue as the leading cause of health facility attendance, high levels of mortality and devastating malaria epidemics in highland areas. Since 2004, Burundi’s National Malaria Control Programme (PNILP) has developed an integrated malaria control strategy. Since 2016, Médecins Sans Frontières (MSF), in collaboration with the PNILP, has implemented integrated malaria control interventions within two malaria endemic health districts located in the central highlands and eastern border regions.
METHODS
We re-assessed epidemiological trends for malaria in Burundi to: (1) evaluate spatial heterogeneity and seasonality; (2) longitudinally describe trends in disease incidence for three epidemiological strata; and (3) assess the association between long-lasting insecticidal net (LLIN) mass distribution campaigns (MDC) and disease incidence. Analysis used malaria case data, routinely collected and reported weekly by PNILP from 2011- 2019. Malaria cases were converted into incidence rates, using existing population data, and expressed per 1000 population at risk. Health districts (n=47) were categorized into three different strata based upon geographic elevation and endemic channels, using the quartile method. A generalized additive mixed model (GAMM) was implemented in R to analyze time-series data.
ETHICS
This work met the requirements for exemption from MSF Ethics Review Board review, and was conducted with permission from Sebastian Spencer, Medical Director, Operational Centre Brussels, MSF.
RESULTS
From 2011-2016, seasonality and intensity of malaria transmission was heterogeneous across the three epidemiological strata. The median incidence (cases/1000 population) for health districts <1200m elevation was 6.0 (interquartile range, IQR, 4.3-8.5); for those 1200-1850m, incidence was 12.3 (IQR 8.0-17.6); and for those >1850m, incidence was 2.1 (IQR 1.1-6.3). In contrast to the observed incidence rates for health districts within the endemic channels at <1200m and >1850m, health districts within the endemic
channel at 1200-1850m showed marked seasonality, with a bimodal distribution. Health districts in these endemic channels, had peaks in median incidence of 17.6 cases/1000 and 15.1cases/1000 population in weeks 26 and 52, respectively. GAMM analysis suggested an increasing trend in malaria incidence over the period 2011—2019. The analysis further revealed that LLIN-MDC campaigns were associated with a rapid reduction in malaria incidence, but the epidemiological impact was attenuated after one year. Specifically, comparing malaria incidence in three health districts adjacent to MSF’s intervention area (1200-1850m channel), the 2017 LLIN-MCD was associated with a 44% reduction in clinical incidence one year post-distribution (RR 0.56, 95%CI 0.556-0.56), but no evidence for a reduction two years post-distribution was observed RR 1.10 (95%CI 1.092-1.099).
CONCLUSION
These findings highlight the effectiveness of LLIN as a malaria control intervention across different epidemiological strata in Burundi. However, the duration of functional effectiveness of LLIN is most definitely less than 3 years and may be shorter than one year in Burundi. The reasons underlying these finding are legion. Further operational research is needed to disentangle the dynamic interplay between operational, human behavioural, sociological, and entomological factors.