Background: The 2018 Physical Activity Guidelines 2nd Edition Advisory Committee Scientific Report recommended research to understand whether the health benefits of physical activity (PA) differed by sociodemographic factors. This study examined associations between meeting PA guidelines in leisure time and all-cause, heart disease, and cancer mortality across sociodemographic characteristics. Methods: Nationally representative data on 567,483 eligible US adults from the 1998-2018 US National Health Interview Survey and 2019 public-use linked mortality files were used. Participants self-reported leisure-time aerobic and muscle-strengthening PA. Meeting PA guidelines was defined as meeting both aerobic and muscle-strengthening activity recommendations. Multivariate Cox regression was used to estimate hazard ratios and 95% confidence intervals comparing all-cause, heart disease, and cancer mortality risk across PA categories, with a focus on adults meeting guidelines. Results: Across sociodemographic groups, associations comparing mortality risk among adults meeting guidelines versus those meeting neither recommendation in leisure time ranged from no significant associations to significant risk reductions in mortality ranging from 14% to 36% for all-cause, 25% to 52% for heart disease, and 20% to 32% for cancer. Risk reductions were larger for women versus men (all cause and heart disease), non-Hispanic or non-Latino/a White adults compared with Hispanic or Latino/a adults (all cause), adults with college education or higher versus those with less than high school education (all cause), and adults with high school education versus those with some college education (cancer). Conclusions: Meeting PA guidelines provides a substantial reduction in mortality risk from all causes, heart disease, and cancer, but the magnitude of reduction may differ across sociodemographic groups.

Introduction: The 2018 Physical Activity Guidelines Advisory Committee Scientific Report called for investigating whether the established health benefits of meeting physical activity guidelines (PAG) differ by sociodemographic factors. Guidelines for adults recommend engaging in muscle-strengthening activities (MSAs; ≥2 days per week) and moderate-to-vigorous aerobic physical activity (MVPA; ≥150 minutes per week at moderate intensity, ≥75 minutes per week at vigorous intensity, or an equivalent combination). Objective: To examine associations between meeting MVPA and MSA guidelines (combined PAG) in leisure time and all-cause and heart disease mortality across sociodemographic factors. Methods: We used nationally representative data on 567,483 adults from the 1998-2018 US National Health Interview Survey (NHIS) and 2019 public-use linked mortality files from the National Death Index. Median follow-up was 9.5 years (range=1-21.8 years). We classified participants into categories (met combined PAG, met MVPA only, met MSA only, met neither) based on reported leisure-time physical activity. We used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between meeting the combined PAG vs. meeting neither guideline and all-cause and heart disease mortality, overall and stratified by sex (women, men), race and ethnicity (six groups), or education (four levels). Models were adjusted for sociodemographic and health factors. We conducted pairwise comparisons (adjusted for multiple comparisons) to determine if associations differed across sociodemographic factors. Results: Compared to meeting neither PAG, meeting the combined PAG was associated with a reduced mortality risk between 14-36% for all-cause mortality and 25-52% for heart disease mortality across sociodemographic groups. Reductions in mortality risk were larger for some groups compared with others. For example, reduction in all-cause mortality was larger for non-Hispanic White compared with Hispanic or Latino adults (HR=0.66 [95% CI: 0.64-0.69] vs. 0.86 [0.75-0.99]; pairwise p <0.001) and for people with more vs. less education (college or more=0.64 [0.60-0.69] vs. less than high school=0.75 [0.69-0.82]; p <0.001). Reduction in heart disease mortality was larger for women compared with men (0.54 [0.48-0.62] vs. 0.66 [0.60-0.73]; p <0.001). Conclusions: Meeting the guidelines for MVPA and MSA generally provides a substantial reduction in risk of all-cause and heart disease mortality. There may be differences in the magnitude of benefit physical activity provides for health across sociodemographic groups. The reasons for these differences are unclear. Identifying factors contributing to these differences would further address research gaps identified in the 2018 Physical Activity Guidelines Advisory Committee Scientific Report.

Targeting malaria interventions in elimination settings where transmission is heterogeneous is essential to ensure the efficient use of resources. Identifying the most important risk factors among persons experiencing a range of exposure can facilitate such targeting. A cross-sectional household survey was conducted in Artibonite, Haiti, to identify and characterize spatial clustering of malaria infections. Household members (N = 21,813) from 6,962 households were surveyed and tested for malaria. An infection was defined as testing positive for Plasmodium falciparum by either a conventional or novel highly sensitive rapid diagnostic test. Seropositivity to the early transcribed membrane protein 5 antigen 1 represented recent exposure to P. falciparum. Clusters were identified using SaTScan. Associations among individual, household, and environmental risk factors for malaria, recent exposure, and living in spatial clusters of these outcomes were evaluated. Malaria infection was detected in 161 individuals (median age: 15 years). Weighted malaria prevalence was low (0.56%; 95% CI: 0.45-0.70%). Serological evidence of recent exposure was detected in 1,134 individuals. Bed net use, household wealth, and elevation were protective, whereas being febrile, over age 5 years, and living in either households with rudimentary wall material or farther from the road increased the odds of malaria. Two predominant overlapping spatial clusters of infection and recent exposure were identified. Individual, household, and environmental risk factors are associated with the odds of individual risk and recent exposure in Artibonite; spatial clusters are primarily associated with household-level risk factors. Findings from serology testing can further strengthen the targeting of interventions.

We propose a censored quantile regression model for the analysis of relative survival data. We create a hybrid data set consisting of the study observations and counterpart randomly sampled pseudopopulation observations imputed from population life tables that adjust for expected mortality. We then fit a censored quantile regression model to the hybrid data incorporating demographic variables (e.g., age, biologic sex, calendar time) corresponding to the population life tables of demographically-similar individuals, a population versus study covariate, and its interactions with the variables of interest. These latter variables can be interpreted as relative survival parameters that depict the differences in failure quantiles between the study participants and their population counterparts.

Capture–recapture methods are widely applied in estimating the number ( ) of prevalent or cumulatively incident cases in disease surveillance. Here, we focus the bulk of our attention on the common case in which there are 2 data streams. We propose a sensitivity and uncertainty analysis framework grounded in multinomial distribution-based maximum likelihood, hinging on a key dependence parameter that is typically nonidentifiable but is epidemiologically interpretable. Focusing on the epidemiologically meaningful parameter unlocks appealing data visualizations for sensitivity analysis and provides an intuitively accessible framework for uncertainty analysis designed to leverage the practicing epidemiologist’s understanding of the implementation of the surveillance streams as the basis for assumptions driving estimation of . By illustrating the proposed sensitivity analysis using publicly available HIV surveillance data, we emphasize both the need to admit the lack of information in the observed data and the appeal of incorporating expert opinion about the key dependence parameter. The proposed uncertainty analysis is a simulation-based approach designed to more realistically acknowledge variability in the estimated associated with uncertainty in an expert’s opinion about the nonidentifiable parameter, together with the statistical uncertainty. We demonstrate how such an approach can also facilitate an appealing general interval estimation procedure to accompany capture–recapture methods. Simulation studies illustrate the reliable performance of the proposed approach for quantifying uncertainties in estimating in various contexts. Finally, we demonstrate how the recommended paradigm has the potential to be directly extended for application to data from >2 surveillance streams.

For a malaria elimination strategy, Haiti's National Malaria Control Program piloted a mass drug administration (MDA) with indoor residual spraying (IRS) in 12 high-transmission areas across five communes after implementing community case management and strengthened surveillance. The MDA distributed sulfadoxine-pyrimethamine and single low-dose primaquine to eligible residents during house visits. The IRS campaign applied pirimiphos-methyl insecticide on walls of eligible houses. Pre- and post-campaign cross-sectional surveys were conducted to assess acceptability, feasibility, drug safety, and effectiveness of the combined interventions. Stated acceptability for MDA before the campaign was 99.2%; MDA coverage estimated at 10 weeks post-campaign was 89.6%. Similarly, stated acceptability of IRS at baseline was 99.9%; however, household IRS coverage was 48.9% because of the high number of ineligible houses. Effectiveness measured by Plasmodium falciparum prevalence at baseline and 10 weeks post-campaign were similar: 1.31% versus 1.43%, respectively. Prevalence of serological markers were similar at 10 weeks post-campaign compared with baseline, and increased at 6 months. No severe adverse events associated with the MDA were identified in the pilot; there were severe adverse events in a separate, subsequent campaign. Both MDA and IRS are acceptable and feasible interventions in Haiti. Although a significant impact of a single round of MDA/IRS on malaria transmission was not found using a standard pre- and post-intervention comparison, it is possible there was blunting of the peak transmission. Seasonal malaria transmission patterns, suboptimal IRS coverage, and low baseline parasitemia may have limited the effectiveness or the ability to measure effectiveness.

(1) Background: Several retrospective observational analyzed treatment outcomes for COVID-19; (2) Methods: Inverse probability of censoring weighting (IPCW) was applied to correct for bias due to informative censoring in database of hospitalized patients who did and did not receive convalescent plasma; (3) Results: When compared with an IPCW analysis, overall mortality was overestimated using an unadjusted Kaplan–Meier curve, and hazard ratios for the older age group compared to the youngest were underestimated using the Cox proportional hazard models and 30-day mortality; (4) Conclusions: An IPCW analysis provided stabilizing weights by hospital admission.

BACKGROUND:The Malaria Frontline Project (MFP) supported the National Malaria Elimination Program for effective program implementation in the high malaria-burden states of Kano and Zamfara adapting the National Stop Transmission of Polio (NSTOP) program elimination strategies.PROJECT IMPLEMENTATION:The MFP was implemented in 34 LGAs in the two states (20 out of 44 in Kano and all 14 in Zamfara). MFP developed training materials and job aids tailored to expected service delivery for primary and district health facilities and strengthened supportive supervision. Pre- and post-implementation assessments of intervention impacts were conducted in both states.RESULTS:A total of 158 (Kano:83; Zamfara:75) and 180 (Kano:100; Zamfara:80) healthcare workers (HCWs), were interviewed for pre-and post-implementation assessments, respectively. The proportions of HCWs with correct knowledge on diagnostic criteria were Kano: 97.5% to 92.0% and Zamfara: 94.7% to 98.8%; and knowledge of recommended first line treatment of uncomplicated malaria were Kano: 68.7% to 76.0% and Zamfara: 69.3% to 65.0%. The proportion of HCWs who adhered to national guidelines for malaria diagnosis and treatment increased in both states (Kano: 36.1% to 73.0%; Zamfara: 39.2% to 67.5%) and HCW knowledge to confirm malaria diagnosis slightly decreased in Kano State but increased in Zamfara State (Kano: 97.5% to 92.0%; Zamfara: 94.8% to 98.8%). HCWs knowledge of correct IPTp drug increased in both states (Kano: 81.9% to 94.0%; Zamfara: 85.3% to 97.5%).CONCLUSION:MFP was successfully implemented using tailored training materials, job aids, supportive supervision, and data use. The project strategy can likely be adapted to improve the effectiveness of malaria program implementation in other Nigerian states, and other malaria endemic countries.

Babesiosis is a tickborne disease caused by intraerythrocytic Babesia parasites. In the United States, most babesiosis cases are caused by Babesia microti, transmitted from bites of blacklegged ticks, Ixodes scapularis, in northeastern and midwestern states. Transmission can also occur through blood transfusions, transplantation of organs from infected donors, or congenital (mother-to-child) transmission (1). Babesia infection can be asymptomatic or cause mild to severe illness that can be fatal. Overall, U.S. tickborne disease cases have increased 25%, from 40,795 reported in 2011 to 50,856 in 2019 (2). Babesiosis trends were assessed in 10 states* where babesiosis was reportable during 2011-2019. Incidence increased significantly in Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont (p<0.001), with the largest increases reported in Vermont (1,602%, from two to 34 cases), Maine (1,422%, from nine to 138), New Hampshire (372%, from 13 to 78), and Connecticut (338%, from 74 to 328). Unlike the other seven states, Maine, New Hampshire, and Vermont, were not included as states with endemic disease in previous CDC babesiosis surveillance summaries. These three states should now be considered to have endemic transmission comparable to that in other high-incidence states; they have consistently identified newly acquired cases every year during 2011-2019 and documented presence of Babesia microti in the associated tick vector (3). Because incidence in Northeastern states, including Maine, New Hampshire, and Vermont, is increasing, tick prevention messaging, provider education, and awareness of infection risk among travelers to these states should be emphasized.

The U.S. Centers for Disease Control and Prevention in collaboration with the National Malaria Elimination Program and the African Field Epidemiology Network established the Malaria Frontline Project to provide innovative approaches to improve the malaria program implementation in Kano and Zamfara States, Nigeria. Innovative approaches such as malaria bulletin, malaria monitoring wall chart, conduct of ward level data validation meetings and malaria dashboard have helped improve the use of data for decision making at all levels. Innovative approaches deployed during the project implementation facilitated data analysis and a better understanding of malaria program performance and data utilization for decision making at all levels. These innovative approaches may improve malaria control program performance in Nigeria and other resource limited countries.

ABSTRACT. Seasonal malaria chemoprevention (SMC) for children under 5 years of age for up to four monthly cycles during malaria transmission season was recommended by the WHO in 2012 and has been implemented in 13 countries in the Sahel, reaching more than 30 million children annually. Malaria control programs implementing SMC have asked the WHO to consider expanding the age range or number of monthly cycles. We conducted a systematic review and meta-analysis of SMC among children up to 15 years of age and up to six monthly cycles. Twelve randomized studies were included, with outcomes stratified by age (< 5/≥ 5 years), by three or four versus five or six cycles, and by drug where possible. Drug regimens included sulfadoxine–pyrimethamine + amodiaquine, amodiaquine–artesunate, and sulfadoxine–pyrimethamine + artesunate. Included studies were all conducted in Sahelian countries in which high-grade resistance to sulfadoxine–pyrimethamine was rare and in zones with parasite prevalence ranging from 1% to 79%. Seasonal malaria chemoprevention resulted in substantial reductions in uncomplicated malaria incidence measured during that transmission season (rate ratio: 0.27, 95% CI: 0.25–0.29 among children < 5 years; rate ratio: 0.27, 95% CI: 0.25–0.30 among children ≥ 5 years) and in the prevalence of malaria parasitemia measured within 4–6 weeks from the final SMC cycle (risk ratio: 0.38, 95% CI: 0.34–0.43 among children < 5 years; risk ratio: 0.23, 95% CI: 0.11–0.48 among children ≥ 5 years). In high-transmission zones, SMC resulted in a moderately reduced risk of any anemia (risk ratio: 0.77, 95% CI: 0.72–0.83 among children < 5 years; risk ratio: 0.70, 95% CI: 0.52–0.95 among children ≥ 5 years [one study]). Children < 10 years of age had a moderate reduction in severe malaria (risk ratio: 0.53, 95% CI: 0.37–0.76) but no evidence of a mortality reduction. The evidence suggests that in areas in which sulfadoxine–pyrimethamine and amodiaquine remained efficacious, SMC effectively reduced malaria disease burden among children both < 5 and ≥ 5 years old and that the number of cycles should be commensurate with the length of the transmission season, up to six cycles.

Background Over the last two decades, the scale-up of vector control and changes in the first-line anti-malarial, from chloroquine (CQ) to sulfadoxine-pyrimethamine (SP) and then to artemether-lumefantrine (AL), have resulted in significant decreases in malaria burden in western Kenya. This study evaluated the long-term effects of control interventions on molecular markers of Plasmodium falciparum drug resistance using parasites obtained from humans and mosquitoes at discrete time points. Methods Dried blood spot samples collected in 2012 and 2017 community surveys in Asembo, Kenya were genotyped by Sanger sequencing for markers associated with resistance to SP ( Pfdhfr, Pfdhps) , CQ, AQ, lumefantrine ( Pfcrt, Pfmdr1) and artemisinin ( Pfk13). Temporal trends in the prevalence of these markers, including data from 2012 to 2017 as well as published data from 1996, 2001, 2007 from same area, were analysed. The same markers from mosquito oocysts collected in 2012 were compared with results from human blood samples. Results The prevalence of SP dhfr/dhps quintuple mutant haplotype C 50 I 51 R 59 N 108 I 164 /S 436 G 437 E 540 A 581 A 613 increased from 19.7% in 1996 to 86.0% in 2012, while an increase in the sextuple mutant haplotype C 50 I 51 R 59 N 108 I 164 / H 436 G 437 E 540 A 581 A 613 containing Pfdhps -436H was found from 10.5% in 2012 to 34.6% in 2017. Resistant Pfcrt -76 T declined from 94.6% in 2007 to 18.3% in 2012 and 0.9% in 2017. Mutant Pfmdr1 -86Y decreased across years from 74.8% in 1996 to zero in 2017, mutant Pfmdr1 -184F and wild Pfmdr1 -D1246 increased from 17.9% to 58.9% in 2007 to 55.9% and 90.1% in 2017, respectively. Pfmdr1 haplotype N 86 F 184 S 1034 N 1042 D 1246 increased from 11.0% in 2007 to 49.6% in 2017. No resistant mutations in Pfk13 were found. Prevalence of Pfdhps -436H was lower while prevalence of Pfcrt- 76 T was higher in mosquitoes than in human blood samples. Conclusion This study showed an increased prevalence of dhfr/dhps resistant markers over 20 years with the emergence of Pfdhps -436H mutant a decade ago in Asembo. The reversal of Pfcrt from CQ-resistant to CQ-sensitive genotype occurred following 19 years of CQ withdrawal. No Pfk13 markers associated with artemisinin resistance were detected, but the increased haplotype of Pfmdr1 N 86 F 184 S 1034 N 1042 D 1246 was observed. The differences in prevalence of Pfdhps -436H and Pfcrt- 76 T SNPs between two hosts and the role of mosquitoes in the transmission of drug resistant parasites require further investigation.

Background Malaria remains a leading cause of morbidity and mortality worldwide, with progress in malaria control stalling in recent years. Proactive community case management (pro-CCM) has been shown to increase access to diagnosis and treatment and reduce malaria burden. However, lack of experimental evidence may hinder the wider adoption of this intervention. We conducted a cluster randomized community intervention trial to assess the efficacy of pro-CCM at decreasing malaria prevalence in rural endemic areas of Madagascar. Methods Twenty-two fokontany (smallest administrative unit) of the Mananjary district in southeast Madagascar were selected and randomized 1:1 to pro-CCM (intervention) or conventional integrated community case management (iCCM). Residents of all ages in the intervention arm were visited by a community health worker every 2 weeks from March to October 2017 and screened for fever; those with fever were tested by a rapid diagnostic test (RDT) and treated if positive. Malaria prevalence was assessed using RDTs on all consenting study area residents prior to and following the intervention. Hemoglobin was measured among women of reproductive age. Intervention impact was assessed via difference-in-differences analyses using logistic regressions in generalized estimating equations. Results A total of 27,087 and 20,475 individuals participated at baseline and endline, respectively. Malaria prevalence decreased from 8.0 to 5.4% in the intervention arm for individuals of all ages and from 6.8 to 5.7% in the control arm. Pro-CCM was associated with a significant reduction in the odds of malaria positivity in children less than 15 years (OR = 0.59; 95% CI [0.38–0.91]), but not in older age groups. There was no impact on anemia among women of reproductive age. Conclusion This trial suggests that pro-CCM approaches could help reduce malaria burden in rural endemic areas of low- and middle-income countries, but their impact may be limited to younger age groups with the highest malaria burden. Trial registration NCT05223933. Registered on February 4, 2022

Objectives: Different methods for detecting Plasmodium parasite infection or exposure are available, but a systematic comparison of all these methodologies to predict malaria infection is lacking. Understanding the characteristics of respective tests is helpful in choosing the most appropriate tests for epidemiological or research purposes. Methods: We performed microscopy, rapid diagnostic tests (RDTs), and polymerase chain reaction (PCR) for 496 patients presenting with febrile illness in Dakar, Senegal, in 2015. Blood samples had laboratory multiplex assays performed for Immunoglobin G serology and detection of histidine-rich protein 2 (HRP2) antigen. Sensitivity (Se) and specificity (Sp) for different tests were calculated using PCR as the gold standard for detecting active infection. Modeling through latent class analysis compared each test to a modeled gold standard for Se/Sp estimates. Results: Against PCR, Se/Sp were 95.2%/93.7% for RDT, 90.4%/100.0% for microscopy, and 97.9%/48.1% for laboratory HRP2 detection. Compared with the modeled gold standard, Se of microscopy was 93.5% and Se of RDT, PCR, and laboratory HRP2 detection were all greater than 99%. Se/Sp of Immunoglobin G serology were substantially lower for detecting active infection. Conclusions: Compared with single tests, a combinatorial latent class analysis approach of multiple biomarkers for detecting malaria infection from patient samples provides greater sensitivity and specificity for epidemiological estimates and research objectives.

As of March 2021, three COVID-19 vaccines had been authorized by the U.S. Food and Drug Administration (FDA) for use in the United States. Each has substantial efficacy in preventing COVID-19. However, as efficacy from trials was <100% for all three vaccines, disease in vaccinated people is expected to occur. We created a spreadsheet-based tool to estimate the number of symptomatic COVID-19 cases among vaccinated people (vaccine breakthrough infections) based on published vaccine efficacy (VE) data, percent of the population that has been fully vaccinated, and average number of COVID-19 cases reported per day. We estimate that approximately 199,000 symptomatic vaccine breakthrough infections (95% CI: ~183,000-214,000 cases) occurred in the United States during January-July 2021 among >156 million fully vaccinated people. With high SARS-CoV-2 transmission and increasing numbers of people vaccinated in the United States, vaccine breakthrough infections will continue to accumulate. Understanding expectations regarding number of vaccine breakthrough infections enables accurate public health messaging to help ensure that the occurrence of such cases does not negatively affect vaccine perceptions, confidence, and uptake.

We fit a Cox proportional hazards (PH) model to interval-censored survival data by first subdividing each individual's failure interval into nonoverlapping sub-intervals. Using the set of all interval endpoints in the data set, those that fall into the individual's interval are then used as the cut points for the sub-intervals. Each sub-interval has an accompanying weight calculated from a parametric Weibull model based on the current parameter estimates. A weighted PH model is then fit with multiple lines of observations corresponding to the sub-intervals for each individual, where the lower end of each sub-interval is used as the observed failure time with the accompanying weights incorporated. Right-censored observations are handled in the usual manner. We iterate between estimating the baseline Weibull distribution and fitting the weighted PH model until the regression parameters of interest converge. The regression parameter estimates are fixed as an offset when we update the estimates of the Weibull distribution and recalculate the weights. Our approach is similar to Satten et al.'s (1998) method for interval-censored survival analysis that used imputed failure times generated from a parametric model in a PH model. Simulation results demonstrate apparently unbiased parameter estimation for the correctly specified Weibull model and little to no bias for a mis-specified log-logistic Corresponding author Email: jow5@cdc.gov 830 AN INTERVAL-CENSORED PROPORTIONAL HAZARDS MODEL model. Breast cosmetic deterioration data and ICU hyperlactemia data are analyzed.

Background. Global gains toward malaria elimination have been heterogeneous and have recently stalled. Interventions targeting afebrile malaria infections may be needed to address residual transmission. We studied the efficacy of repeated rounds of community-based mass testing and treatment (MTaT) on malaria infection prevalence in western Kenya. Methods. Twenty clusters were randomly assigned to 3 rounds of MTaT per year for 2 years or control (standard of care for testing and treatment at public health facilities along with government-sponsored mass long-lasting insecticidal net [LLIN] distributions). During rounds, community health volunteers visited all households in intervention clusters and tested all consenting individuals with a rapid diagnostic test. Those positive were treated with dihydroartemisinin-piperaquine. Cross-sectional community infection prevalence surveys were performed in both study arms at baseline and each year after 3 rounds of MTaT. The primary outcome was the effect size of MTaT on parasite prevalence by microscopy between arms by year, adjusted for age, reported LLIN use, enhanced vegetative index, and socioeconomic status. Results. Demographic and behavioral characteristics, including LLIN usage, were similar between arms at each survey. MTaT coverage across the 3 annual rounds ranged between 75.0% and 77.5% in year 1, and between 81.9% and 94.3% in year 2. The adjusted effect size of MTaT on the prevalence of parasitemia between arms was 0.93 (95% confidence interval [CI], .79-1.08) and 0.92 (95% CI, .76-1.10) after year 1 and year 2, respectively. Conclusions. MTaT performed 3 times per year over 2 years did not reduce malaria parasite prevalence in this high-transmission area.

Sample size and power calculations are often based on a two-group comparison. However, in some instances the group membership cannot be ascertained until after the sample has been collected. In this situation, the respective sizes of each group may not be the same as those prespecified due to binomial variability, which results in a difference in power from that expected. Here we suggest that investigators calculate an “expected power” taking into account the binomial variability of the group member ship, and adjust the sample size accordingly when planning such studies. We explore different scenarios where such an adjustment may or may not be necessary for both continuous and binary responses. In general, the number of additional subjects required depends only slightly on the values of the (standardized) difference in the two group means or proportions, but more importantly on the respective sizes of the group membership. We present tables with adjusted sample sizes for a variety of scenarios that can be readily used by investigators at the study design stage. The proposed approach is motivated by a genetic study of cerebral malaria and a sleep apnea study.

We present power calculations for zero-inflated Poisson (ZIP) and zero-inflated negative-binomial (ZINB) models. We detail direct computa- tions for a ZIP model based on a two-sample Wald test using the expected information matrix. We also demonstrate how Lyles, Lin, and Williamson's method (2006) of power approximation for categorical and count outcomes can be extended to both zero-inflated models. This method can be used for power calculations based on the Wald test (via the observed information matrix) and the likelihood ratio test, and can accommodate both categori- cal and continuous covariates. All the power calculations can be conducted when covariates are used in the modeling of both the count data and the "excess zero" data, or in either part separately. We present simulations to detail the performance of the power calculations. Analysis of a malaria study is used for illustration.