Comparison of test-negative and syndrome-negative controls in SARS-CoV-2 vaccine effectiveness evaluations for preventing COVID-19 hospitalizations in the United States

BackgroundTest-negative design (TND) studies have produced validated estimates of vaccine effectiveness (VE) for influenza vaccine studies. However, syndrome-negative controls have been proposed for differentiating bias and true estimates in VE evaluations for COVID-19. To understand the use of alternative control groups, we compared characteristics and VE estimates of syndrome-negative and test-negative VE controls.MethodsAdults hospitalized at 21 medical centers in 18 states March 11–August 31, 2021 were eligible for analysis. Case patients had symptomatic acute respiratory infection (ARI) and tested positive for SARS-CoV-2. Control groups were test-negative patients with ARI but negative SARS-CoV-2 testing, and syndrome-negative controls were without ARI and negative SARS-CoV-2 testing. Chi square and Wilcoxon rank sum tests were used to detect differences in baseline characteristics. VE against COVID-19 hospitalization was calculated using logistic regression comparing adjusted odds of prior mRNA vaccination between cases hospitalized with COVID-19 and each control group.Results5811 adults (2726 cases, 1696 test-negative controls, and 1389 syndrome-negative controls) were included. Control groups differed across characteristics including age, race/ethnicity, employment, previous hospitalizations, medical conditions, and immunosuppression. However, control-group-specific VE estimates were very similar. Among immunocompetent patients aged 18–64 years, VE was 93 % (95 % CI: 90–94) using syndrome-negative controls and 91 % (95 % CI: 88–93) using test-negative controls.ConclusionsDespite demographic and clinical differences between control groups, the use of either control group produced similar VE estimates across age groups and immunosuppression status. These findings support the use of test-negative controls and increase confidence in COVID-19 VE estimates produced by test-negative design studies.     

Validity of the estimates of oral cholera vaccine effectiveness derived from the test-negative design

BackgroundThe test-negative design (TND) has emerged as a simple method for evaluating vaccine effectiveness (VE). Its utility for evaluating oral cholera vaccine (OCV) effectiveness is unknown. We examined this method's validity in assessing OCV effectiveness by comparing the results of TND analyses with those of conventional cohort analyses.MethodsRandomized controlled trials of OCV were conducted in Matlab (Bangladesh) and Kolkata (India), and an observational cohort design was used in Zanzibar (Tanzania). For all three studies, VE using the TND was estimated from the odds ratio (OR) relating vaccination status to fecal test status (Vibrio cholerae O1 positive or negative) among diarrheal patients enrolled during surveillance (VE =  (1 − OR)×100%). In cohort analyses of these studies, we employed the Cox proportional hazard model for estimating VE (=1 − hazard ratio)×100%).ResultsOCV effectiveness estimates obtained using the TND (Matlab: 51%, 95% CI:37–62%; Kolkata: 67%, 95% CI:57–75%) were similar to the cohort analyses of these RCTs (Matlab: 52%, 95% CI:43–60% and Kolkata: 66%, 95% CI:55–74%). The TND VE estimate for the Zanzibar data was 94% (95% CI:84–98%) compared with 82% (95% CI:58–93%) in the cohort analysis. After adjusting for residual confounding in the cohort analysis of the Zanzibar study, using a bias indicator condition, we observed almost no difference in the two estimates.ConclusionOur findings suggest that the TND is a valid approach for evaluating OCV effectiveness in routine vaccination programs.     

A comparison of the test-negative and traditional case-control study designs with respect to the bias of estimates of rotavirus vaccine effectiveness

Estimation of the effectiveness of rotavirus vaccines via the test-negative control study design has gained popularity over the past few years. In this study design, children with severe diarrhea who test positive for rotavirus infection are considered as cases, while children who test negative serve as controls. We use a simple probability model to evaluate and compare the test-negative control and the traditional case-control designs with respect to the bias of resulting estimates of rotavirus vaccine effectiveness (VE). Comparisons are performed under two scenarios, corresponding to studies performed in high-income and low-income countries. We consider two potential sources of bias: (a) misclassification bias resulting from imperfect sensitivity and specificity of the test used to diagnose rotavirus infection, and (b) selection bias associated with possible effect of rotavirus vaccination on the probability of contracting severe non-rotavirus diarrhea.Our results suggest that both sources of bias may produce VE estimates with substantial bias. Particularly, lack of perfect specificity is associated with severe negative bias. For example, if the specificity of the diagnostic test is 90% then VE estimates from both types of case-control studies may under-estimate the true VE by more than 20%. If the vaccine protects children against non-rotavirus diarrhea then VE estimates from test-negative control studies may be close to zero even though the true VE is 50%. However, the sensitivity and specificity of the enzyme immunoassay test currently used to diagnose rotavirus infections are both over 99%, and there is no solid evidence that the existing rotavirus vaccines affect the rates of non-rotavirus diarrhea. We therefore conclude that the test-negative control study design is a convenient and reliable alternative for estimation of rotavirus VE.     

Effect of propensity of seeking medical care on the bias of the estimated effectiveness of rotavirus vaccines from studies using a test-negative case-control design

BackgroundRotavirus is the leading cause of severe diarrhea among children worldwide, and vaccines can reduce morbidity and mortality by 50–98%. The test-negative control (TNC) study design is increasingly used for evaluating the effectiveness of vaccines against rotavirus and other vaccine-preventable diseases. In this study design, symptomatic patients who seek medical care are tested for the pathogen of interest. Those who test positive (negative) are classified as cases (controls).MethodsWe use a probability model to evaluate the bias of estimates of rotavirus vaccine effectiveness (VE) against rotavirus diarrhea resulting in hospitalization in the presence of possible confounding and selection biases due to differences in the propensity of seeking medical care (PSMC) between vaccinated and unvaccinated children.ResultsThe TNC-based VE estimate corrects for confounding bias when the confounder’s effects on the probabilities of rotavirus and non-rotavirus related hospitalizations are equal. If this condition is not met, then the estimated VE may be substantially biased. The bias is more severe in low-income countries, where VE is known to be lower. Under our model, differences in PSMC between vaccinated and unvaccinated children do not result in selection bias when the TNC study design is used.ConclusionsIn practice, one can expect the association of PSMC (or other potential confounders) with the probabilities of rotavirus and non-rotavirus related hospitalization to be similar, in which case the confounding effects will only result in small bias in the VE estimate from TNC studies. The results of this work, along with those of our previous paper, confirm the TNC design can be expected to provide reliable estimates of rotavirus VE in both high- and low-income countries.     

The impact of selection bias on vaccine effectiveness estimates from test-negative studies

IntroductionEstimates of vaccine effectiveness (VE) from test-negative studies may be subject to selection bias. In the context of influenza VE, we used simulations to identify situations in which meaningful selection bias can occur. We also analyzed observational study data for evidence of selection bias.MethodsFor the simulation study, we defined a hypothetical population whose members are at risk for acute respiratory illness (ARI) due to influenza and other pathogens. An unmeasured “healthcare seeking proclivity” affects both probability of vaccination and probability of seeking care for an ARI. We varied the direction and magnitude of these effects and identified situations where meaningful bias occurred. For the observational study, we reanalyzed data from the United States Influenza VE Network, an ongoing test-negative study. We compared “bias-naïve” VE estimates to bias-adjusted estimates, which used data from the source populations to correct for sampling bias.ResultsIn the simulation study, an unmeasured care-seeking proclivity could create selection bias if persons with influenza ARI were more (or less) likely to seek care than persons with non-influenza ARI. However, selection bias was only meaningful when rates of care seeking between influenza ARI and non-influenza ARI were very different. In the observational study, the bias-naïve VE estimate of 55% (95% CI, 47-–62%) was trivially different from the bias-adjusted VE estimate of 57% (95% CI, 49-–63%).ConclusionsIn combination, these studies suggest that while selection bias is possible in test-negative VE studies, this bias in unlikely to be meaningful under conditions likely to be encountered in practice. Researchers and public health officials can continue to rely on VE estimates from test-negative studies.     

Rotavirus vaccine effectiveness in low-income settings: An evaluation of the test-negative design

BackgroundThe test-negative design (TND), an epidemiologic method currently used to measure rotavirus vaccine (RV) effectiveness, compares the vaccination status of rotavirus-positive cases and rotavirus-negative controls meeting a pre-defined case definition for acute gastroenteritis. Despite the use of this study design in low-income settings, the TND has not been evaluated to measure rotavirus vaccine effectiveness.MethodsThis study builds upon prior methods to evaluate the use of the TND for influenza vaccine using a randomized controlled clinical trial database. Test-negative vaccine effectiveness (VE-TND) estimates were derived from three large randomized placebo-controlled trials (RCTs) of monovalent (RV1) and pentavalent (RV5) rotavirus vaccines in sub-Saharan Africa and Asia. Derived VE-TND estimates were compared to the original RCT vaccine efficacy estimates (VE-RCTs). The core assumption of the TND (i.e., rotavirus vaccine has no effect on rotavirus-negative diarrhea) was also assessed.ResultsTND vaccine effectiveness estimates were nearly equivalent to original RCT vaccine efficacy estimates. Neither RV had a substantial effect on rotavirus-negative diarrhea.ConclusionsThis study supports the TND as an appropriate epidemiologic study design to measure rotavirus vaccine effectiveness in low-income settings.     

Sample size considerations for mid-season estimates from a large influenza vaccine effectiveness network in the United States

IntroductionMid-season influenza vaccine effectiveness (VE) estimates are a useful tool to help guide annual influenza vaccine strain selection, vaccine policy, and public health messaging. We propose using a sample size-driven approach with data-driven inputs for publication of mid-season influenza VE.MethodsWe used pooled inputs for VE by (sub)type and average vaccine coverage by age groups using data from eight seasons of the US Influenza VE Network to calculate sample sizes needed to estimate mid-season VE.ResultsWe estimate that 135 influenza-positive cases would be needed to detect an overall VE of 40% with 55% vaccine coverage among test-negative controls. Larger sample sizes would be required to produce reliable estimates specifically against influenza A/H3N2 and for older age groups.ConclusionUsing an existing network, most of the recent influenza seasons in the US would facilitate valid mid-season VE estimates using the proposed sample sizes for broad age groupings.     

Influenza vaccine effectiveness by test-negative design – Comparison of inpatient and outpatient settings

BackgroundObservational studies of influenza vaccine effectiveness (VE) are increasingly using the test-negative design. Studies are typically based in outpatient or inpatient settings, but these two approaches are rarely compared directly. The aim of our study was to assess whether influenza VE estimates differ between inpatient and outpatient settings.MethodsWe searched the literature from Medline, PubMed and Web of Science using a combination of keywords to identify published studies of influenza VE using the test-negative design. Studies assessing any type of influenza vaccine among any population in any setting were considered, while interim studies or re-analyses were excluded. Retrieved articles were reviewed, screened and categorized based on study setting, location and influenza season. We searched for parallel studies in inpatient and outpatient settings that were done in the same influenza season, in the same location, and in the same or similar age groups. For each of the pairs identified, we estimated the difference in VE estimates between settings, and we tested whether the average difference was significant using a paired t-test.ResultsIn total 25 pairs of estimates were identified that permitted comparisons between VE estimates in inpatient and outpatient study settings. Within pairs, the prevalence of influenza was generally higher among patients enrolled in the outpatient studies, while influenza vaccination coverage among the test-negative control groups was generally higher in the inpatient studies. There was no heterogeneity in the paired differences in VE, and the pooled difference in VE between inpatient and outpatient studies was −2% (95% confidence interval: −12%, 10%).ConclusionsWe found no differences in VE estimates between inpatient and outpatient settings by studies using the test-negative design. Further research involving direct comparisons of VE estimates from the two settings in the same populations and years would be valuable.     

The case test-negative design for studies of the effectiveness of influenza vaccine

Background

A modification to the case–control study design has become popular to assess vaccine effectiveness (VE) against viral infections. Subjects with symptomatic illness seeking medical care are tested by a highly specific polymerase chain reaction (PCR) assay for the detection of the infection of interest. Cases are subjects testing positive for the virus; those testing negative represent the comparison group. Influenza and rotavirus VE studies using this design are often termed “test-negative case-control” studies, but this design has not been formally described or evaluated. We explicitly state several assumptions of the design and examine the conditions under which VE estimates derived with it are valid and unbiased.

Methods

We derived mathematical expressions for VE estimators obtained using this design and examined their statistical properties. We used simulation methods to test the validity of the estimators and illustrate their performance using an influenza VE study as an example.

Results

Because the marginal ratio of cases to non-cases is unknown during enrollment, this design is not a traditional case-control study; we suggest the name “case test-negative” design. Under sets of increasingly general assumptions, we found that the case test-negative design can provide unbiased VE estimates. However, differences in health care-seeking behavior among cases and non-cases by vaccine status, strong viral interference, or modification of the probability of symptomatic illness by vaccine status can bias VE estimates.

Conclusions

Vaccine effectiveness estimates derived from case test-negative studies are valid and unbiased under a wide range of assumptions. However, if vaccinated cases are less severely ill and seek care less frequently than unvaccinated cases, then an appropriate adjustment for illness severity is required to avoid bias in effectiveness estimates. Viral interference will lead to a non-trivial bias in the vaccine effectiveness estimate from case test-negative studies only when incidence of influenza is extremely high and duration of transient non-specific immunity is long.     

Influenza vaccine effectiveness against hospitalization with laboratory-confirmed influenza in Greece: A pooled analysis across six seasons, 2013–2014 to 2018–2019

BackgroundMonitoring seasonal influenza Vaccine Effectiveness (VE) is key to inform vaccination strategies and sustain uptake. Pooling data across multiple seasons increases precision and allows for subgroup analyses, providing more conclusive evidence. Our aim was to assess VE against hospitalization with laboratory-confirmed influenza in Greece over six seasons, from 2013 to 2014 to 2018–2019, using routinely collected surveillance data.MethodsSwab samples from hospitalized patients across the country were tested for influenza by RT-PCR. We used the test-negative design, with patients testing positive for influenza serving as cases and those testing negative serving as controls. VE was calculated as one minus the Odds Ratio (OR) for influenza vaccination, estimated by mixed-effects logistic regression and adjusted for age, sex, hospitalization type (being in intensive care or not), time from symptom onset to swabbing, and calendar time. Stratified estimates by age and hospitalization type were obtained, and also subgroup estimates by influenza type/subtype and season. Antigenic and genetic characterization of a subset of circulating influenza strains was performed.ResultsA total of 3,882 test-positive cases and 5,895 test-negative controls were analyzed. Across all seasons, adjusted VE was 45.5% (95% CI: 31.6–56.6) against all influenza, 62.8% against A(H1N1)pdm09 (95% CI: 40.7–76.7), 28.2% against A(H3N2) (95% CI: 12.0–41.3) and 45.5% against influenza B (95% CI: 29.1–58.1). VE was slightly lower for patients aged 60 years and over, and similar between patients hospitalized inside or outside intensive care. Circulating A(H1N1)pdm09 and B strains were antigenically similar to the vaccine strains, whereas A(H3N2) were not.ConclusionOur results confirm the public health benefits from seasonal influenza vaccination, despite the suboptimal effectiveness against A(H3N2) strains. Continued monitoring of VE is essential, and routinely collected surveillance data can be valuable in this regard.     

Diarrheal disease risk in Matlab, Bangladesh.

The objective of this research project is to assess risk for diarrheal disease in rural Bangladesh by analyzing the complex and dynamic interaction of biological, socioeconomic, cultural/behavioral and environmental factors over time and space. Risk factors of cholera and non-cholera water diarrheal disease are calculated to compare the relative importance of risk for several independent variables. Diarrheal disease data were collected for people who were hospitalized at the International Centre for Diarrhoeal Disease Research (ICDDR) hospital from January 1, 1992 to December 31, 1994. Using laboratory and hospital records, cases were assigned to one of two diarrhea disease categories (cholera or non-cholera watery diarrhea) that were used as dependent variables in the analysis stage of the research. Age-matched individuals were randomly chosen from the community to be controls. Information was collected for independent variables that were hypothesized to be related to watery diarrhea. This information was collected by administering questionnaires, obtaining secondary data from the ICDDR's demographic surveillance system records and community health worker record books and calculating variables using a geographic information system database. Sanitation and water availability and use are extremely important in the effort to reduce secondary cholera and non-cholera, watery diarrhea transmission. Water use and availability variables were more important for non-cholera watery diarrheal risk than for cholera but nevertheless they were important for both. Socioeconomic status is an important indirect cause of both of these diseases because poverty is the root cause of many of the other variables, such as lack of sanitation and clean water. Flood-control was related to both types of diarrhea but it is not understood why. Since the Bangladesh Flood Action Plan will continue to build and maintains flood-control embankments, it is important to investigate whether there is a pattern to this relationship throughout the country and to investigate why the relationship exists.     

Interim influenza vaccine effectiveness: A good proxy for final estimates in Spain in the seasons 2010–2014

IntroductionThe agreement between interim and final influenza vaccine effectiveness (VE) estimates would support the use of interim assessments as a proxy for final VE results to guide health authorities in influenza prevention. We aimed to compare interim/final VE estimates in Spain.MethodsWe used a test-negative case-control study (cycEVA) for 2010/11–2013/14 seasons. Sensitivity analyses were carried out by type/subtype of influenza virus and by target groups for vaccination.ResultsIn general, interim estimates were higher compared to end-season estimates. Interim and final VE differences were higher for the target groups compared to all population. Subtype-specific interim/final VE estimates showed greater concordance (3–13%) than for any virus (7–24%).ConclusionIn Spain, interim influenza VE estimates over 2010–2014 were a good proxy of the final protection of the vaccine. Interim and final estimates showed greater concordance for all population and if performed subtype-specific.     

On the bias of estimates of influenza vaccine effectiveness from test–negative studies

Estimates of the effectiveness of influenza vaccines are commonly obtained from a test-negative design (TND) study, where cases and controls are patients seeking care for an acute respiratory illness who test positive and negative, respectively, for influenza infection. Vaccine effectiveness (VE) estimates from TND studies are usually interpreted as vaccine effectiveness against medically-attended influenza (MAI). However, it is also important to estimate VE against any influenza illness (symptomatic influenza (SI)) as individuals with SI are still a public health burden even if they do not seek medical care. We present a numerical method to evaluate the bias of TND-based estimates of influenza VE with respect to MAI and SI. We consider two sources of bias: (a) confounding bias due to a (possibly unobserved) covariate that is associated with both vaccination and the probability of the outcome of interest and (b) bias resulting from the effect of vaccination on the probability of seeking care. Our results indicate that (a) VE estimates may suffer from substantial confounding bias when a confounder has a different effect on the probabilities of influenza and non-influenza ARI, and (b) when vaccination reduces the probability of seeking care against influenza ARI, then estimates of VE against MAI may be unbiased while estimates of VE against SI may be have a substantial positive bias.     

Feasibility of case-control and test-negative designs to evaluate dengue vaccine effectiveness in Malaysia

BackgroundThe world’s first dengue vaccine [Dengvaxia; Sanofi Pasteur] was licensed in 2015 and others are in development. Real-world evaluations of dengue vaccines will therefore soon be needed. We assessed feasibility of case control (CC) and test-negative (TN) design studies for dengue vaccine effectiveness by measuring associations between socio-demographic risk factors, and hospitalized dengue outcomes, in Malaysia.MethodsFollowing ethical approval, we conducted hospital-based dengue surveillance for one year in three referral hospitals. Suspected cases aged 9–25 years underwent dengue virological confirmation by RT-PCR and/or NS1 Ag ELISA at a central laboratory. Two age- and geography-matched hospitalized non-dengue case-controls were recruited for a traditional CC study. Suspected cases testing negative were test-negative controls. Socio-demographic, risk factor and routine laboratory data were collected. Logistic regression models were used to estimate associations between confirmed dengue and risk factors.ResultsWe recruited 327 subjects; 155 were suspected of dengue. The planned sample size was not met. 124 (80%) of suspected cases were dengue-confirmed; seven were assessed as severe. Three had missing RT-PCR results; the study recruited 28 test-negative controls. Only 172 matched controls could be recruited; 90 cases were matched with ≥1 controls. Characteristics of cases and controls were mostly similar. By CC design, two variables were significant risk factors for hospitalized dengue: recent household dengue contact (OR: 54, 95% CI: 7.3–397) and recent neighbourhood insecticidal fogging (OR: 2.1; 95% CI: 1.3–3.6). In the TN design, no risk factors were identified. In comparison with gold-standard diagnostics, routine tests performed poorly.ConclusionsThe CC design may be more appropriate than the TN design for hospitalized dengue vaccine effectiveness studies. Selection bias in case control selection could be minimized by protocol changes more easily than increasing TN design control numbers, because early-stage dengue diagnosis in endemic countries is highly specific. MREC study approval: (39)KKM/NIHSEC/P16-1334.     

Effectiveness of an oral cholera vaccine campaign to prevent clinically-significant cholera in Odisha State,India

BackgroundA clinical trial conducted in India suggests that the oral cholera vaccine, Shanchol, provides 65% protection over five years against clinically-significant cholera. Although the vaccine is efficacious when tested in an experimental setting, policymakers are more likely to use this vaccine after receiving evidence demonstrating protection when delivered to communities using local health department staff, cold chain equipment, and logistics.MethodsWe used a test-negative, case-control design to evaluate the effectiveness of a vaccination campaign using Shanchol and validated the results using a cohort approach that addressed disparities in healthcare seeking behavior. The campaign was conducted by the local health department using existing resources in a cholera-endemic area of Puri District, Odisha State, India. All non-pregnant residents one year of age and older were offered vaccine. Over the next two years, residents seeking care for diarrhea at one of five health facilities were asked to enroll following informed consent. Cases were patients seeking treatment for laboratory-confirmed V. cholera-associated diarrhea. Controls were patients seeking treatment for V. cholerae negative diarrhea.ResultsOf 51,488 eligible residents, 31,552 individuals received one dose and 23,751 residents received two vaccine doses. We identified 44 V. cholerae O1-associated cases and 366 non V. cholerae diarrhea controls. The adjusted protective effectiveness for persons receiving two doses was 69.0% (95% CI: 14.5% to 88.8%), which is similar to the adjusted estimates obtained from the cohort approach. A statistical trend test suggested a single dose provided a modicum of protection (33%, test for trend, p = 0.0091).ConclusionThis vaccine was found to be as efficacious as the results reported from a clinical trial when administered to a rural population using local health personnel and resources. This study provides evidence that this vaccine should be widely deployed by public health departments in cholera endemic areas.     

Vaccine effectiveness against COVID-19 related hospital admission in the Netherlands: A test-negative case-control study

IntroductionReal-world vaccine effectiveness (VE) estimates are essential to identify potential groups at higher risk of break-through infections and to guide policy. We assessed the VE of COVID-19 vaccination against COVID-19 hospitalization, while adjusting and stratifying for patient characteristics.MethodsWe performed a test-negative case-control study in six Dutch hospitals. The study population consisted of adults eligible for COVID-19 vaccination hospitalized between May 1 and June 28, 2021 with respiratory symptoms. Cases were defined as patients who tested positive for SARS-CoV-2 by PCR during the first 48 h of admission or within 14 days prior to hospital admission. Controls were patients tested negative at admission and did not have a positive test during the 2 weeks prior to hospitalization. VE was calculated using multivariable logistic regression, adjusting for calendar week, sex, age, comorbidity and nursing home residency. Subgroup analysis was performed for age, sex and different comorbidities. Secondary endpoints were ICU-admission and mortality.Results379 cases and 255 controls were included of whom 157 (18%) were vaccinated prior to admission. Five cases (1%) and 40 controls (16%) were fully vaccinated (VE: 93%; 95% CI: 81 – 98), and 40 cases (11%) and 70 controls (27%) were partially vaccinated (VE: 70%; 95% CI: 50–82). A strongly protective effect of vaccination was found in all comorbidity subgroups. No ICU-admission or mortality were reported among fully vaccinated cases. Of unvaccinated cases, mortality was 10% and 19% was admitted at the ICU.ConclusionCOVID-19 vaccination provides a strong protective effect against COVID-19 related hospital admission, in patients with and without comorbidity.     

A rapid qualitative assessment of oral cholera vaccine anticipated acceptability in a context of resistance towards cholera intervention in Nampula,Mozambique

IntroductionWhile planning an immunization campaign in settings where public health interventions are subject to politically motivated resistance, designing context-based social mobilization strategies is critical to ensure community acceptability. In preparation for an Oral Cholera Vaccine campaign implemented in Nampula, Mozambique, in November 2016, we assessed potential barriers and levers for vaccine acceptability.MethodsQuestionnaires, in-depth interviews, and focus group discussions, as well as observations, were conducted before the campaign. The participants included central and district level government informants (national immunization program, logistics officers, public health directors, and others), community leaders and representatives, and community members.ResultsDuring previous well chlorination interventions, some government representatives and health agents were attacked, because they were believed to be responsible for spreading cholera instead of purifying the wells. Politically motivated resistance to cholera interventions resurfaced when an OCV campaign was considered. Respondents also reported vaccine hesitancy related to experiences of problems during school-based vaccine introduction, rumors related to vaccine safety, and negative experiences following routine childhood immunization. Despite major suspicions associated with the OCV campaign, respondents’ perceived vulnerability to cholera and its perceived severity seem to override potential anticipated OCV vaccine hesitancy.DiscussionPotential hesitancy towards the OCV campaign is grounded in global insecurity, social disequilibrium, and perceived institutional negligence, which reinforces a representation of estrangement from the central government, triggering suspicions on its intentions in implementing the OCV campaign. Recommendations include a strong involvement of community leaders, which is important for successful social mobilization; representatives of different political parties should be equally involved in social mobilization efforts, before and during campaigns; and public health officials should promote other planned interventions to mitigate the lack of trust associated with perceived institutional negligence. Successful past initiatives include public intake of purified water or newly introduced medication by social mobilizers, teachers or credible leaders.     

The test-negative design for estimating influenza vaccine effectiveness

Objective

The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed.

Methods

In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative.

Results

With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time.

Conclusions

The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata.     

Lineage-matched versus mismatched influenza B vaccine effectiveness following seasons of marginal influenza B circulation

BackgroundSeveral countries have recently transitioned from the trivalent inactivated influenza vaccine (TIV) to the quadrivalent inactivated influenza vaccine (QIV) in order to outweigh influenza B vaccine-mismatch. However, few studies thus far evaluated its benefits versus the TIV in a systematic manner. Our objective was to compare the QIV VE with lineage-mismatched TIV VE.MethodsWe estimated the 2015–2016, 2017–2018, 2019–2020 end-of season influenza B VE against laboratory-confirmed influenza-like illness (ILI) among community patients, using the test-negative design. VE was estimated for pre-determined age groups and for moving age intervals of 15 years.ResultsSince 2011–2012 season, alternate seasons in Israel were dominated by influenza B circulation. Compared with the lineage-mismatched TIV used during the 2015–2016 and 2017–2018 seasons, the 2019–2020 QIV showed the highest all-ages VE, with VE estimates of 56.9 (95% CI 30.1 to 73.4), 16.5 (95% CI –22.5 to 43.1) and ?25.8 (95% CI ?85.3 to 14.6) for the 2019–2020, 2017–2018 and 2015–2016 seasons, respectively. The 2019–2020 VE point estimated were the highest for the 0.5–4, 5–17 and 18–44 years age groups and for more 15-year age intervals as compared to the other seasons.ConclusionsOur results support the rapid transition from the TIV to the QIV.