Assessing the Relationship Between Gravidity and Placental Malaria Among Pregnant Women in a High Transmission Area in Ghana

Background Malaria infection during pregnancy can cause significant morbidity and mortality to a pregnant woman, her foetus and newborn. In areas of high endemic transmission, gravidity is an important risk factor for infection, but there is a complex relationship with other exposure-related factors, and use of protective measures. This study investigated the association between gravidity and placental malaria (PM), among pregnant women aged 14-49 in Kintampo, a high transmission area of Ghana. Methods Between 2008-2011, as part of a study investigating the association between PM and malaria in infancy, pregnant women attending antenatal care (ANC) clinics in the study area were enrolled and followed up until delivery. The outcome of PM was assessed at delivery by placental histopathology. Multivariable logistic regression analyses were used to investigate the association between gravidity and PM, identify other key risk factors, and control for potential confounders. Pre-specified effect modifiers including area of residence, socio-economic score (SES), ITN use and IPTp-SP use were explored. Results The prevalence of PM was 65.9% in primigravidae, and 26.5% in multigravidae. After adjusting for age, SES and relationship status, primigravidae were shown to have over three times the odds of PM compared to multigravidae, defined as women with 2 or more previous pregnancies (adjusted OR=3.36 (95% CI 2.39-4.71), N=1808, P<0.001). The association appeared stronger in rural areas (OR for PG vs. MG was 3.79 (95% CI: 3.61-5.51) in rural areas; 2.09 (95% CI: 1.17- 3.71) in urban areas; P for interaction =0.07), and among women with lower socio-economic scores (OR for PG vs. MG was 4.73 (95% CI 3.08-7.25) amongst women with lower SES; OR=2.14 (95% CI 1.38-3.35) among women with higher SES; P for interaction =0.008. There was also evidence of lower risk among primigravidae with better use of the current preventive measures IPTp and LLIN. Conclusions The burden of PM is most heavily focused on primigravidae of low SES living in rural areas of high transmission. Programmes should prioritize primigravidae and young women of child-bearing age for interventions such as LLIN distribution, educational initiatives and treatment to reduce the burden of malaria in first pregnancy.

Insecticide resistance and behavioural adaptation as a response to long-lasting insecticidal net deployment in malaria vectors in the Cascades region of Burkina Faso

The decline in malaria across Africa has been largely attributed to vector control using long-lasting insecticidal nets (LLINs). However, this intervention has prompted widespread insecticide resistance (IR) and been associated with changes in mosquito behaviour that reduce their contact with LLINs. The relative importance and rate at which IR and behavioural adaptations emerge are poorly understood. We conducted surveillance of mosquito behaviour and IR at 12 sites in Burkina Faso to assess the magnitude and temporal dynamics of insecticide, biting and resting behaviours in vectors in the 2-year period following mass LLIN distribution. Insecticide resistance was present in all vector populations and increased rapidly over the study period. In contrast, no longitudinal shifts in LLIN-avoidance behaviours (earlier or outdoor biting and resting) were detected. There was a moderate but statistically significant shift in vector species composition from Anopheles coluzzii to Anopheles gambiae which coincided with a reduction in the proportion of bites preventable by LLINs; possibly driven by between-species variation in behaviour. These findings indicate that adaptations based on insecticide resistance arise and intensify more rapidly than behavioural shifts within mosquito vectors. However, longitudinal shifts in mosquito vector species composition were evident within 2 years following a mass LLIN distribution. This ecological shift was characterized by a significant increase in the exophagic species (An. gambiae) and coincided with a predicted decline in the degree of protection expected from LLINs. Although human exposure fell through the study period due to reducing vector densities and infection rates, such ecological shifts in vector species along with insecticide resistance were likely to have eroded the efficacy of LLINs. While both adaptations impact malaria control, the rapid increase of the former indicates this strategy develops more quickly in response to selection from LLINS. However, interventions targeting both resistance strategies will be needed.

Insecticide resistance outpaces behavioural adaptation, as a response to Long-Lasting Insecticidal Net distribution, in malaria vectors in Burkina Faso

The decline in malaria across Africa has been largely attributed to vector control using Long-Lasting Insecticidal Nets (LLINs). However, this intervention has prompted widespread insecticide resistance (IR) and been associated with changes in mosquito behaviour that reduce their contact with LLINs. The relative importance and rate at which IR and behavioural adaptations emerge are poorly understood. We conducted surveillance of mosquito behaviour and IR at 12 sites in Burkina Faso to assess the magnitude and temporal dynamics of insecticide and behavioural resistance in vectors in the 2-year following mass LLIN distribution. Insecticide resistance was present in all vector populations and increased rapidly over the study. In contrast, no longitudinal shifts in LLIN-avoidance behaviours (earlier or outdoor biting and resting) were detected. There was a moderate shift in vector species composition from Anopheles coluzzii to Anopheles gambiae which coincided with a reduction in the proportion of bites preventable by LLINs; possibly driven by between-species variation in behaviour. These findings indicate that adaptations based on insecticide resistance arise and intensify more rapidly than behavioural shifts within mosquito vectors. However, longitudinal shifts in mosquito vector species composition were evident within 2 years following a mass LLIN distribution. This ecological shift was characterized by a relative increase in the moderately more exophagic species (An. gambiae) and coincided with a predicted decline in the degree of protection expected from LLINs. Although human exposure fell through the study period due to reducing vector densities and infection rates, such ecological shifts in vector species along with insecticide resistance were likely to have eroded the efficacy of LLINs. While both adaptations impact malaria control, the rapid increase of the former indicates it is the most rapid strategy but interventions targeting both will be needed.

Impact of seasonality and malaria control interventions on Anopheles density and species composition from three areas of Uganda with differing malaria endemicity

Background Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are the malaria control interventions primarily responsible for reductions in transmission intensity across sub-Saharan Africa. These interventions, however, may have differential impact on Anopheles species composition and density. This study examined the changing pattern of Anopheles species in three areas of Uganda with markedly different transmission intensities and different levels of vector control. Methods From October 2011 to June 2016 mosquitoes were collected monthly using CDC light traps from 100 randomly selected households in three areas: Walukuba (low transmission), Kihihi (moderate transmission) and Nagongera (high transmission). LLINs were distributed in November 2013 in Walukuba and Nagongera and in June 2014 in Kihihi. IRS was implemented only in Nagongera, with three rounds of bendiocarb delivered between December 2014 and June 2015. Mosquito species were identified morphologically and by PCR (Polymerase Chain Reaction). Results In Walukuba, LLIN distribution was associated with a decline in Anopheles funestus vector density (0.07 vs 0.02 mosquitoes per house per night, density ratio [DR] 0.34, 95% CI: 0.18–0.65, p = 0.001), but not Anopheles gambiae sensu stricto (s.s.) nor Anopheles arabiensis. In Kihihi, over 98% of mosquitoes were An. gambiae s.s. and LLIN distribution was associated with a decline in An. gambiae s.s. vector density (4.00 vs 2.46, DR 0.68, 95% CI: 0.49–0.94, p = 0.02). In Nagongera, the combination of LLINs and multiple rounds of IRS was associated with almost complete elimination of An. gambiae s.s. (28.0 vs 0.17, DR 0.004, 95% CI: 0.002–0.009, p < 0.001), and An. funestus sensu lato (s.l.) (3.90 vs 0.006, DR 0.001, 95% CI: 0.0005–0.004, p < 0.001), with a less pronounced decline in An. arabiensis (9.18 vs 2.00, DR 0.15 95% CI: 0.07–0.33, p < 0.001). Conclusions LLIN distribution was associated with reductions in An. funestus s.l. in the lowest transmission site and An. gambiae s.s. in the moderate transmission site. In the highest transmission site, a combination of LLINs and multiple rounds of IRS was associated with the near collapse of An. gambiae s.s. and An. funestus s.l. Following IRS, An. arabiensis, a behaviourally resilient vector, became the predominant species, which may have implications for malaria vector control activities. Development of interventions targeted at outdoor biting remains a priority.

Insecticide resistance outpaces behavioural adaptation, as a response to Long-Lasting Insecticidal Net distribution, in malaria vectors in Burkina Faso.

The decline in malaria across Africa has been largely attributed to vector control using Long-Lasting Insecticidal Nets (LLINs). However, this intervention has prompted widespread insecticide resistance (IR) and been associated with changes in mosquito behaviour that reduce their contact with LLINs. The relative importance and rate at which IR and behavioural adaptations emerge are poorly understood. We conducted surveillance of mosquito behaviour and IR at 12 sites in Burkina Faso to assess the magnitude and temporal dynamics of insecticide and behavioural resistance in vectors in the 2-year following mass LLIN distribution. Insecticide resistance was present in all vector populations and increased rapidly over the study. In contrast, no longitudinal shifts in LLIN-avoidance behaviours (earlier or outdoor biting and resting) were detected. There was a moderate shift in vector species composition from Anopheles coluzzii to Anopheles gambiae which coincided with a reduction in the proportion of bites preventable by LLINs; possibly driven by between-species variation in behaviour. These findings indicate that adaptations based on insecticide resistance arise and intensify more rapidly than behavioural shifts within mosquito vectors. However, longitudinal shifts in mosquito vector species composition were evident within 2 years following a mass LLIN distribution. This ecological shift was characterized by a relative increase in the moderately more exophagic species (An. gambiae) and coincided with a predicted decline in the degree of protection expected from LLINs. Although human exposure fell through the study period due to reducing vector densities and infection rates, such ecological shifts in vector species along with insecticide resistance were likely to have eroded the efficacy of LLINs. While both adaptations impact malaria control, the rapid increase of the former indicates it is the most rapid strategy but interventions targeting both will be needed.

Impact of seasonality and malaria control interventions on Anopheles density and species composition from three areas of Uganda with differing malaria endemicity.

Background Long lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are malaria control interventions primarily responsible for reductions in transmission intensity across sub-Saharan Africa. These interventions, however, may have differential impact on Anopheles species composition and density. Here, we studied the changing pattern of Anopheles species in three areas of Uganda with markedly different transmission intensities and different levels of vector control. Methods From October 2011 to June 2016 mosquitoes were collected monthly using CDC light traps from 100 randomly selected households in three areas: Walukuba (low transmission), Kihihi (moderate transmission) and Nagongera (high transmission). LLINs were distributed in November 2013 in Walukuba and Nagongera and in June 2014 in Kihihi. IRS was implemented only in Nagongera, with three rounds of bendiocarb delivered between December 2014 and June 2015. Mosquito species were identified morphologically and by PCR (Polymerase Chain Reaction). Results In Walukuba, LLIN distribution was associated with a decline in Anopheles funestus vector density (0.07 vs 0.02 mosquitoes per house per night, density ratio [DR] 0.34, 95% CI: 0.18-0.65, p=0.001), but not An. gambiae s.s. nor An. arabiensis. In Kihihi, over 98% of mosquitoes were An. gambiae s.s. and LLIN distribution was associated with a decline in An. gambiae s.s. vector density (4.00 vs 2.46, DR 0.68, 95% CI: 0.49-0.94, p=0.02). In Nagongera, the combination of LLINs and multiple rounds of IRS was associated with almost complete elimination of An. gambiae s.s. (28.0 vs 0.17, DR 0.004, 95% CI: 0.002-0.009, p<0.001), and An. funestus s.l. (3.90 vs 0.006, DR 0.001, 95% CI: 0.0005-0.004, p<0.001), with a less pronounced decline in An. arabiensis (9.18 vs 2.00, DR 0.15 95% CI: 0.07-0.33, p<0.001). Conclusions LLIN distribution was associated with reductions in An. funestus s.l. in the lowest transmission site and An. gambiae s.s. in the moderate transmission site. In the highest transmission site, a combination of LLINs and multiple rounds of IRS was associated with the near collapse of An. gambiae s.s. and An. funestus s.l. Following IRS, An. arabiensis, a behaviorally resilient vector, became the predominant species, which may have implications for malaria vector control activities. Development of interventions targeted at outdoor biting remains a priority.

Impact of Seasonality and Malaria Control Interventions on Anopheles Density and Species Composition From Three Areas of Uganda With Differing Malaria Endemicity.

Background Long lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are malaria control interventions primarily responsible for reductions in transmission intensity across sub-Saharan Africa. These interventions, however, may have differential impact on Anopheles species composition and density. Here, we studied the changing pattern of Anopheles species in three areas of Uganda with markedly different transmission intensities and different levels of vector control.Methods From October 2011 to June 2016 mosquitoes were collected monthly using CDC light traps from 100 randomly selected households in three areas: Walukuba (low transmission), Kihihi (moderate transmission) and Nagongera (high transmission). LLINs were distributed in November 2013 in Walukuba and Nagongera and in June 2014 in Kihihi. IRS was implemented only in Nagongera, with three rounds of bendiocarb delivered between December 2014 and June 2015. Mosquito species were identified morphologically and by PCR (Polymerase Chain Reaction). Results In Walukuba, LLIN distribution was associated with a decline in Anopheles funestus vector density (0.07 vs 0.02 mosquitoes per house per night, density ratio [DR] 0.34, 95% CI: 0.18-0.65, p=0.001), but not An. gambiae s.s. nor An. arabiensis. In Kihihi, over 98% of mosquitoes were An. gambiae s.s. and LLIN distribution was associated with a decline in An. gambiae s.s. vector density (4.00 vs 2.46, DR 0.68, 95% CI: 0.49-0.94, p=0.02). In Nagongera, the combination of LLINs and multiple rounds of IRS was associated with almost complete elimination of An. gambiae s.s. (28.0 vs 0.17, DR 0.004, 95% CI: 0.002-0.009, p<0.001), and An. funestus s.l. (3.90 vs 0.006, DR 0.001, 95% CI: 0.0005-0.004, p<0.001), with a less pronounced decline in An. arabiensis (9.18 vs 2.00, DR 0.15 95% CI: 0.07-0.33, p<0.001). Conclusions LLIN distribution was associated with reductions in An. funestus s.l. in the lowest transmission site and An. gambiae s.s. in the moderate transmission site. In the highest transmission site, a combination of LLINs and multiple rounds of IRS was associated with the near collapse of An. gambiae s.s. and An. funestus s.l. Following IRS, An. arabiensis, a behaviorally resilient vector, became the predominant species, which may have implications for malaria vector control activities.

Impact of mass distribution of long-lasting insecticidal nets (LLINs) in Mozambique, 2011 to 2025: Retrospective and prospective modeling of child mortality and lives saved

Background Malaria was the leading cause of post-neonatal deaths in Mozambique in 2017. The use of long-lasting insecticidal nets (LLINs) is recognized as one of the most effective ways to reduce malaria morbidity and mortality, especially in children. In 2015, Mozambique committed to the expansion of LLIN coverage nationwide, culminating in the first countrywide campaign in 2017, reaching 95% of registered households. Between 2012 and 2019, more than 34 million LLINs were distributed. No previous analyses have estimated changes in mortality attributable to the scale-up of LLINs, accounting for provincial differences in mortality rates and coverage of health interventions. Methods From 2012 to 2020, the population-based model NetCALC was used to predict provincial household LLIN coverage based upon the number of LLINs distributed annually. NetCALC also projected how many LLINs are needed to maintain universal coverage in 10 provinces from 2021 to 2025. Based upon the annual provincial coverage of LLINs, the Lives Saved Tool (LiST), a multi-cause mathematical model, estimated under-5 lives saved, and reductions in under-5 mortality attributable to LLIN expansion in 10 provinces of Mozambique between 2012 and 2020, and projected lives saved from 2021 to 2025 if universal coverage of LLINs is sustained. Results Results from the LiST models estimate that 64,470 child deaths were averted between 2012 and 2019. If currently planned quantities of LLINs are distributed in 2020, and universal coverage is maintained from 2021 to 2025, an additional 68,695 child deaths could be averted. From 2011 to 2020, the percent reduction in all-cause child mortality was 19.2%, from 114.5 per 1,000 to 93.2 per 1000 in the LLIN distribution model compared to 9.5% in the baseline model. If universal coverage continues through 2025, this reduction will be sustained. Conclusions LiST and NetCALC used together are useful in estimating lives saved and mortality in countries such as Mozambique where vital registration data to measure changes in mortality are not consistently available. Universal coverage of LLINs can save a substantial number of child lives and reduce child mortality in Mozambique but will require resource mobilization. Without continued investment, thousands of avoidable child deaths will occur.

Coverage outcomes (effects), costs, cost-effectiveness, and equity of two combinations of long-lasting insecticidal net (LLIN) distribution channels in Kenya: a two-arm study under operational conditions

Background Malaria-endemic countries distribute long-lasting insecticidal nets (LLINs) through combined channels with ambitious, universal coverage (UC) targets. Kenya has used eight channels with variable results. To inform national decision-makers, this two-arm study compares coverage (effects), costs, cost-effectiveness, and equity of two combinations of LLIN distribution channels in Kenya. Methods Two combinations of five delivery channels were compared as ‘intervention’ and ‘control’ arms. The intervention arm comprised four channels: community health volunteer (CHV), antenatal and child health clinics (ANCC), social marketing (SM) and commercial outlets (CO). The control arm consisted of the intervention arm channels except mass campaign (MC) replaced CHV. Primary analysis used random sample household survey data, service-provider costs, and voucher or LLIN distribution data to compare between-arm effects, costs, cost-effectiveness, and equity. Secondary analyses compared costs and equity by channel. Results The multiple distribution channels used in both arms of the study achieved high LLIN ownership and use. The intervention arm had significantly lower reported LLIN use the night before the survey (84·8% [95% CI 83·0–86·4%] versus 89·2% [95% CI 87·8–90·5%], p < 0·0001), higher unit costs ($10·56 versus $7·17), was less cost-effective ($86·44, 95% range $75·77–$102·77 versus $69·20, 95% range $63·66–$77·23) and more inequitable (Concentration index [C.Ind] = 0·076 [95% CI 0·057 to 0·095 versus C.Ind = 0.049 [95% CI 0·030 to 0·067]) than the control arm. Unit cost per LLIN distributed was lowest for MC ($3·10) followed by CHV ($10·81) with both channels being moderately inequitable in favour of least-poor households. Conclusion In line with best practices, the multiple distribution channel model achieved high LLIN ownership and use in this Kenyan study setting. The control-arm combination, which included MC, was the most cost-effective way to increase UC at household level. Mass campaigns, combined with continuous distribution channels, are an effective and cost-effective way to achieve UC in Kenya. The findings are relevant to other countries and donors seeking to optimise LLIN distribution. Trial registration The assignment of the intervention was not at the discretion of the investigators; therefore, this study did not require registration.

Intensity of pyrethroid resistance in Anopheles gambiae before and after a mass distribution of insecticide-treated nets in Kinshasa and in 11 provinces of the Democratic Republic of Congo

Background: Between 2011 and 2018, an estimated 134.8 million pyrethroid-treated long-lasting insecticidal nets (LLINs) were distributed nationwide in the Democratic Republic of Congo (DRC) for malaria control. Pyrethroid resistance has developed in DRC in recent years, but the intensity of resistance and impact on LLIN efficacy was not known. Therefore, the intensity of resistance of Anopheles gambiae sensu lato (s.l.) to permethrin and deltamethrin was monitored before and after a mass distribution of LLINs in Kinshasa in December 2016, and in 7 sites across the country in 2017 and 11 sites in 2018.Methods: In Kinshasa, CDC bottle bioassays using 1, 2, 5, and 10 times the diagnostic dose of permethrin and deltamethrin were conducted using An. gambiae s.l. collected as larvae and reared to adults. Bioassays were conducted in four sites in Kinshasa province six months before a mass distribution of deltamethrin-treated ITNs and then two, six, and ten months after the distribution. One site in neighbouring Kongo Central province was used as a control (no mass campaign of ITN distribution during the study). Nationwide intensity assays were conducted in six sites in 2017 using CDC bottle bioassays and in 11 sites in 2018 using WHO intensity assays. A sub-sample of An. gambiae s.l. was tested by PCR to determine species composition and frequency of kdr-1014F and 1014S alleles. Results: In June 2016, before LLIN distribution, permethrin resistance intensity was high in Kinshasa; the mean mortality rate was 43% at the 5× concentration and 73% at the 10× concentration. Bioassays at 3 time points after LLIN distribution showed considerable variation by site and time and there was no consistent evidence for an increase in pyrethroid resistance intensity compared to the neighbouring control site. Tests of An. gambiae s.l. in 7 sites across the country in 2017 and 11 sites in 2018 showed all populations were resistant to the diagnostic doses of 3 pyrethroids. In 2018, the intensity of resistance varied by site, but was generally moderate for all three pyrethroids, with survivors at ×5 the diagnostic dose. Anopheles gambiae sensu stricto (s.s.) was the most common species identified across 11 sites in DRC, but in Kinshasa, An. gambiae s.s. (91%) and Anopheles coluzzii (8%) were sympatric.Conclusions: Moderate or high intensity pyrethroid resistance was detected nationwide in DRC and is a serious threat to sustained malaria control with pyrethroid LLINs. Next generation nets (PBO nets or bi-treated nets) should be considered for mass distribution.