An Adaptive Intervention Trial Design for Finding the Optimal Integrated Strategies for Malaria Control and Elimination in Africa: A Model Simulation Study

2021 ◽  
Author(s):  
Guofa Zhou ◽  
Ming-chieh Lee ◽  
Xiaoming Wang ◽  
Daibin Zhong ◽  
Elizabeth Hemming-Schroeder ◽  
...  
Keyword(s):  
Trial Design ◽  
Model Simulation ◽  
Indoor Residual Spraying ◽  
Field Trials ◽  
Outcome Variable ◽  
Relative Reduction ◽  
Infection Prevalence ◽  
Adaptive Intervention ◽  
New Strategy ◽  
Adaptive Trial Design

There are a number of available and emerging malaria intervention tools that require innovative trial designs to find the optimal combinations at given epidemiologic settings. We simulated intervention strategies based on adaptive interventions, which included long-lasting insecticidal nets (LLINs), piperonyl butoxide–treated LLINs (PBO-LLINs), indoor residual spraying (IRS), and long-lasting microbial larviciding (LLML). The aims were to determine if PBO-LLINs or LLIN+IRS combination is more effective for initial interventions than LLINs and to identify the most effective intervention. We used a clustered, randomized adaptive trial design with malaria infection prevalence (MIP) as the outcome variable. The results indicate that during the initial stage of interventions, compared with regular LLINs, PBO-LLINs (relative reduction [RR]: 29.3%) and LLIN plus IRS with alternative-insecticide (RR: 26.8%) significantly reduced MIP. In the subsequent interventions, adding alternative insecticide IRS (RR: 23.8%) or LLML (RR: 31.2%) to existing PBO-LLIN was effective in further reducing MIP. During the next stage of interventions, adding LLML on top of PBO-LLIN+IRS (with alternative insecticides) had a significant impact on MIP (RR: 39.2%). However, adding IRS (with alternative insecticides) on top of PBO-LLIN+LLML did not significantly reduce MIP (11.6%). Overall, in clusters initiated with PBO-LLIN, adding LLML would be the most effective strategy in reducing MIP; in clusters initiated with LLIN+IRS, replacing LLIN+IRS with PBO-LLIN and LLML would be the most effective in reducing MIP. This study provides a new pathway for informing the optimal integrated malaria vector interventions, and the new strategy can be tested in field trials.

scholarly journals Bayesian adaptive trial design in acute heart failure syndromes: Moving beyond the mega trial

2012 ◽  
Vol 164 (2) ◽  
pp. 138-145 ◽  
Author(s):  
Sean P. Collins ◽  
Christopher J. Lindsell ◽  
Peter S. Pang ◽  
Alan B. Storrow ◽  
W. Frank Peacock ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Trial Design ◽  
Adaptive Trial Design ◽  
Acute Heart Failure Syndromes ◽  
Adaptive Trial

scholarly journals The FDA adaptive trial design guidance in a nutshell - A review in Q&A format for decision makers

2016 ◽  
Author(s):  
Klaus Gottlieb
Keyword(s):  
Trial Design ◽  
Adaptive Design ◽  
Decision Makers ◽  
Development Programs ◽  
Fda Guidance ◽  
Regulatory Affairs ◽  
Frequent Use ◽  
Adaptive Trial Design ◽  
Adaptive Trial ◽  
Design Guidance

The FDA adaptive trial design guidance (1) is a thoughtful but lengthy document that explains on 50 pages wide-ranging and important topics “such as ... what aspects of adaptive design trials (i.e., clinical, statistical, regulatory) call for special consideration, ... when to interact with FDA while planning and conducting adaptive design studies, ... what information to include in the adaptive design for FDA review, and ... issues to consider in the evaluation of a completed adaptive design study.” [20-24]. The advice in the guidance is often misinterpreted, misquoted or ignored. This is unfortunate because an appropriate use of adaptive designs could increase the chances of success in drug development programs. Decision makers rely on the advice of regulatory affairs professionals and statisticians to interpret the guidance. Unfortunately, many clinical trial statisticians and regulatory professionals only have a rudimentary understanding of the guidance, presumably because the document is somewhat inscrutable for both audiences, too ‘regulatory’ for statisticians, too ‘statistical’ for regulatory people. This digest was therefore written with three goals in mind: 1) Make the content of the guidance more accessible through a question & answer format, 2) shorten the content from 50 to 10 pages by excerpting the most important dictums, and 3) keep fidelity to the original guidance by frequent use of direct quotes with reference to the respective lines in the original FDA guidance where the quote can be found in square brackets.

scholarly journals The FDA adaptive trial design guidance in a nutshell - A review in Q&A format for decision makers

2016 ◽  
Author(s):  
Klaus Gottlieb
Keyword(s):  
Trial Design ◽  
Adaptive Design ◽  
Decision Makers ◽  
Development Programs ◽  
Fda Guidance ◽  
Regulatory Affairs ◽  
Frequent Use ◽  
Adaptive Trial Design ◽  
Adaptive Trial ◽  
Design Guidance

The FDA adaptive trial design guidance (1) is a thoughtful but lengthy document that explains on 50 pages wide-ranging and important topics “such as ... what aspects of adaptive design trials (i.e., clinical, statistical, regulatory) call for special consideration, ... when to interact with FDA while planning and conducting adaptive design studies, ... what information to include in the adaptive design for FDA review, and ... issues to consider in the evaluation of a completed adaptive design study.” [20-24]. The advice in the guidance is often misinterpreted, misquoted or ignored. This is unfortunate because an appropriate use of adaptive designs could increase the chances of success in drug development programs. Decision makers rely on the advice of regulatory affairs professionals and statisticians to interpret the guidance. Unfortunately, many clinical trial statisticians and regulatory professionals only have a rudimentary understanding of the guidance, presumably because the document is somewhat inscrutable for both audiences, too ‘regulatory’ for statisticians, too ‘statistical’ for regulatory people. This digest was therefore written with three goals in mind: 1) Make the content of the guidance more accessible through a question & answer format, 2) shorten the content from 50 to 10 pages by excerpting the most important dictums, and 3) keep fidelity to the original guidance by frequent use of direct quotes with reference to the respective lines in the original FDA guidance where the quote can be found in square brackets.

scholarly journals Asymptomatic and Submicroscopic Plasmodium Infections in an Area Before and During Integrated Vector Control in Homa Bay, Western Kenya

2022 ◽  
Author(s):  
Collince Jared Omondi ◽  
Otambo O Wilfred ◽  
David Odongo ◽  
Kevin O. Ochwedo ◽  
Antony Otieno ◽  
...  
Keyword(s):  
Vector Control ◽  
Blood Smear ◽  
Geometric Mean ◽  
Indoor Residual Spraying ◽  
Infection Prevalence ◽  
Cross Sectional ◽  
Western Kenya ◽  
Primary Vector ◽  
Asymptomatic Infections ◽  
The Impact

Abstract Background Long lasting insecticidal bednets (LLINs) have been the primary vector control strategy until indoor residual spraying (IRS) was added in Homa Bay and Migori Counties in western Kenya. The objective of this study was to evaluate the impact of LLINs integrated with organophosphate-based (Actellic 300 CS) IRS on the prevalence of asymptomatic and submicroscopic Plasmodium species infections in Homa Bay County. Methods Four consecutive community cross-sectional surveys for Plasmodium species infection were conducted in residents of Homa Bay County, Kenya commencing immediately before and 2 years after introduction of annual IRS. Finger-prick blood samples were obtained to prepare thick and thin smears for microscopic determination and qPCR diagnosis of Plasmodium genus, P. falciparum, P. malariae and P. ovale infection. Results Plasmodium spp. infection prevalence by microscopy was 18.5% before IRS and 14.2%, 3.3% and 1.3% after two annual rounds of IRS (χ²= 186.9, df = 3, p < 0.0001). Submicroscopic (blood smear negative, qPCR positive) parasitemia was 50.4% before IRS and 43.2%, 68.0% and 80.7% after IRS (χ²= 31.98, df = 3, p < 0.0001). Geometric mean density of P. falciparum parasitemia decreased over the 2-year study period (ANOVA, F = 28.95, df = 3, 243, p < 0.0001). The proportion of blood smear positive asymptomatic infections that included P. falciparum did not significantly change over the study period. In contrast, the proportion of asymptomatic submicroscopic P. falciparum infections trended upward following introduction of IRS (pre-IRS 48.2% versus post-IRS 41.6%, 61.3% and 75.4%; (χ²= 24.00, df = 3, p = 0.0002). Conclusions These data suggest that two annual rounds of IRS integrated with LLIN significantly reduced the prevalence of Plasmodium parasitemia, whereas the proportion of submicroscopic infections that included P. falciparum parasite increases. Strategies that aim at reducing the number of asymptomatic submicroscopic infections should be considered to diminish cryptic P. falciparum transmission and enhance malaria control.

scholarly journals Prevalence and Risk Factors Associated with Malaria among Children Aged Six Months to 14 Years Old in Rwanda: Evidence from 2017 Rwanda Malaria Indicator Survey

2020 ◽  
Vol 17 (21) ◽  
pp. 7975
Author(s):  
Faustin Habyarimana ◽  
Shaun Ramroop
Keyword(s):  
Age Groups ◽  
Construction Materials ◽  
Indoor Residual Spraying ◽  
Outcome Variable ◽  
Bed Nets ◽  
Factors Associated ◽  
Malaria Indicator Survey ◽  
Complex Design ◽  
Poor Families ◽  
Household Members

Malaria is a major public health risk in Rwanda where children and pregnant women are most vulnerable. This infectious disease remains the main cause of morbidity and mortality among children in Rwanda. The main objectives of this study were to assess the prevalence of malaria among children aged six months to 14 years old in Rwanda and to identify the factors associated with malaria in this age group. This study used data from the 2017 Rwanda Malaria Indicator Survey. Due to the complex design used in sampling, a survey logistic regression model was used to fit the data and the outcome variable was the presence or absence of malaria. This study considered 8209 children in the analysis and the prevalence of malaria was 14.0%. This rate was higher among children aged 5–9 years old (15.6%), compared to other age groups. Evidently, the prevalence of malaria was also higher among children from poor families (19.4%) compared to children from the richest families (4.3%). The prevalence of malaria was higher among children from rural households (16.2%) compared to children from urban households (3.4%). The results revealed that other significant factors associated with malaria were: the gender of the child, the number of household members, whether the household had mosquito bed nets for sleeping, whether the dwelling had undergone indoor residual spraying in the 12 months prior to the survey, the location of the household’s source of drinking water, the main wall materials of the dwelling, and the age of the head of the household. The prevalence of malaria was also high among children living in houses with walls built from poorly suited materials; this suggests the need for intervention in construction materials. Further, it was found that the Eastern Province also needs special consideration in malaria control due to the higher prevalence of the disease among its residents, compared to those in other provinces.

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