Human Respiratory Syncytial Virus (HRSV) is a leading cause of respiratory infections in young children. HRSV cases declined dramatically in the initial stages of the COVID-19 pandemic, followed by a resurgence in 2022/2023. To investigate patterns of viral genetic diversity and evolutionary dynamics during this period, HRSV sequences were analyzed at national and global levels, including newly sequenced samples from pediatric patients at a major Florida medical center in Alachua County. Our Florida strains clustered within multiple clades, with no clear association between specific clades and clinical or epidemiologic characteristics. Phylodynamic analyses suggested post-pandemic changes in HRSV-A and HRSV-B population dynamics, while phylogeographic patterns were compatible with possible viral introductions from European countries. We also detected amino acid diversity in known G-protein epitope regions, indicating a genetic variation in antigenically relevant sites. These findings suggest that post-pandemic HRSV circulation was associated with changes in viral population dynamics and genetic diversity, emphasizing the value of continued genomic surveillance to monitor viral evolution and support future prevention strategies.

Infants represent a vulnerable population for severe outcomes from infectious diseases. For dengue virus, maternal antibodies can cause severe disease in infants aged 5-12 months through antibody-dependent enhancement, but the role of maternal immunity in neonates aged 0-30 days has not been quantified. Our study leverages the re-emerging setting of Brazil, where the proportion of mothers with anti-dengue antibodies varies across space and time. Infant dengue burden has risen 11-fold from 2000-2024, in line with expansion in the general population. We fit mechanistic models to infant dengue and severe dengue cases reported through surveillance to disentangle the competing roles of maternal immunity, transmission, and age on the risk of dengue and severe dengue in infants across the first year of life. We observed peaks in severe dengue risk in neonates and at 7-8 months of age. These two peaks were explained by competing mechanisms. Infants born to seropositive mothers had lower overall risk of dengue, but increased risk of severe disease from 5-12 months, than those born to seronegative mothers. As dengue incidence increases, and vaccination becomes available, maternal antibodies may decrease infant burden but increase the risk of severe disease.

Importance:In December 2025, the Advisory Committee on Immunization Practices (ACIP) voted to replace the universal hepatitis B birth-dose recommendation with shared clinical decision-making for infants born to mothers who screen negative for hepatitis B surface antigen. Although the proposal would not alter recommendations for infants of unscreened mothers, historical data suggest that removing a universal birth-dose vaccine recommendation may reduce vaccination coverage in this group. Objective:To estimate the impact of replacing universal hepatitis B virus (HBV) birth-dose vaccination with a targeted recommendation on neonatal and subsequent chronic HBV infections in the US. Design, Setting, and Participants:A compartmental model and simulated a US birth cohort (n = 3 659 289) under the 2 vaccine recommendations: universal birth-dose vaccination and targeted birth-dose vaccination vaccine recommendations, where the birth dose was recommended to infants of screened-positive or unscreened mothers and shared-decision making is recommended for infants of screened-negative mothers. Parameter values were literature derived and uncertainty was incorporated across 5000 iterations. These data were analyzed from September through November 2025. Exposures:Birth-dose vaccine recommendations and birth-dose vaccination coverage among infants of unscreened mothers. Main Outcomes and Measures:Numbers of neonatal and subsequent chronic HBV infections. Results:With the current maternal HBV screening rate of 86%, the universal birth-dose vaccine recommendation resulted in a median of 1292 neonatal infections (95% percentile interval [PI], 670-2228). In comparison, the targeted birth-dose vaccine recommendation was associated with 628 additional neonatal infections (95% PI, 340-1034) when birth-dose vaccination coverage among infants of unscreened mothers was 10% (mirroring historic coverage declines under a targeted recommendation) and 69 additional infections (95% PI, -32 to 190) when coverage was 80% (mirroring levels under a universal recommendation.) To offset the excess infections under the targeted birth-dose vaccine recommendation, more than 100 000 additional pregnant individuals would need to be screened if the birth-dose vaccination coverage among infants of unscreened mothers was 80%, and more than 400 000 if coverage was 10%. Conclusions and Relevance:Findings from this study indicate that the targeted birth-dose vaccine recommendation will likely increase neonatal infections unless maternal screening rises substantially or vaccination coverage among infants of unscreened mothers exceeds current levels. As historic data show such improvements are unlikely, these findings underscore the continued importance of universal screening and vaccination as complementary safeguards.

The test-negative design (TND) has become a widely used observational study design for evaluating vaccine effectiveness, especially during the COVID-19 pandemic. Traditionally, TND has been viewed as a variant of the case-control study and largely limited to use with logistic regression models. In this paper, we first establish that TND can be framed as a special case of a cohort study, thereby opening the door to a wider range of analytical approaches. We then introduce the Prentice, Williams, and Peterson gap-time (PWP-GT) frailty model as a novel method for analyzing TND data, accounting for recurrent infections and time-dependent vaccination status. Through extensive simulation studies, we demonstrate that the proposed model outperforms conventional models commonly applied in TND-based vaccine effectiveness studies. Finally, we apply our method to data from the National COVID Cohort Collaborative, estimating the effectiveness of full and booster doses of Pfizer's COVID-19 vaccines against both initial infection and reinfection during the Omicron variant circulation period in a real-world setting.

Background Dengue is a growing global health threat. Our initial evaluation of the TAK-003 dengue vaccine in adolescents during the 2024 outbreak in São Paulo State, Brazil, showed short-term protection but suggested possible effectiveness waning after 90-days of the first dose, and had limited power to estimate second-dose effectiveness against hospitalisation. We evaluated 1-year vaccine effectiveness against symptomatic, virologically confirmed dengue and dengue hospitalisation in adolescents during 2024–2025, when DENV-1 and DENV-2 predominated in 2024 followed by increasing DENV-3 transmission in 2025. Methods We did a test-negative case–control study among adolescents aged 10–15 years in São Paulo State between Feb 20, 2024, and Dec 31, 2025. We extracted individual-level information on demographic characteristics, comorbidities, dengue testing, dengue vaccination, hospitalisation, and death during the study period from the national surveillance databases for dengue (SINAN-Dengue; compulsory notification) and the São Paulo State Secretary of Health vaccination registry (Rede Nacional de Dados em Saúde) on Feb 4, 2026. Cases were defined as acute febrile illness episodes with virologically confirmed dengue, as detected by NS1 antigen or RT-PCR testing within 5 days of symptom onset. Controls were test-negative acute febrile illness episodes. Surveillance data were linked to the state vaccination registry. Vaccine effectiveness after one or two TAK-003 doses was estimated with mixed-effects logistic regression. Findings We analysed 166,390 tests: 65,365 from cases and 101,025 from controls. Vaccine effectiveness against symptomatic dengue was 59.2% (95% CI 56.1–62.0) after one dose and 73.1% (69.1–76.6) after two doses. Against dengue hospitalisation, effectiveness was 74.6% (62.7–82.7) after one dose and 87.9% (73.0–94.6) after two doses. One-dose protection against symptomatic disease showed no evidence of waning over 1-year follow-up: effectiveness was 73.8% (64.7–80.6) at 270–364 days and 76.8% (59.3–86.8) at 365 days or more. Two-dose protection remained stable to 1 year (74.6%, 95% CI 59.0–84.2, at 270–365 days). Findings were robust in sensitivity analyses and comparable during increased DENV-3 circulation. Interpretation Our findings show that TAK-003 demonstrated sustained 1-year protection against symptomatic dengue and dengue hospitalisation in adolescents during a large outbreak. Notably, a single dose showed sustained effectiveness without evidence of waning over 1 year, generating an important hypothesis regarding dose reduction that warrants continued long-term observational evaluation. A second dose provided optimal protection, particularly against hospitalisation. These findings reinforce the importance of dengue vaccination as a public health measure. Funding National Council for Scientific and Technological Development.

Dengue virus (DENV) circulates in two distinct transmission cycles: one, termed the sylvatic cycle, is enzootic to canopy-living hosts, including non-human primates and primatophilic mosquitoes, and the other, initiated by spillover from the sylvatic cycle, is endemic to humans and anthropophilic mosquitoes. Transmission dynamics of sylvatic DENV in non-human hosts has not been well characterized, and the identity of reservoir and amplification hosts is still to be determined. We investigated the role of the three common species of monkeys in the Kédougou region of Senegal in the sylvatic transmission cycle of DENV. Longitudinal surveillance of primatophilic mosquitoes in this region dating back to the 1970s revealed that sylvatic DENV-2, the only one of the four DENV serotypes found to circulate in a sylvatic transmission in West Africa, is amplified cyclically at intervals of approximately eight years based on the isolation of the virus from mosquitoes. Subsequent to the detection of DENV-2 in primatophilic mosquitoes in Kédougou in 2008, 737 monkeys, including 3 species: Chlorocebus sabaeus (n = 219), Erythrocebus patas (n = 78), and Papio papio (n = 440) were captured from 2010 to 2012 for the current study. Their age was determined using dentition and other morphological measurements. Evidence of DENV-2 infection was detected via neutralizing antibody in sera, and the annual hazard of DENV-2 infection was estimated per species using catalytic models. These analyses revealed annual hazard ranging from 0.09 to 0.42 across the three species, consistent with high levels of transmission in these populations. Furthermore, seroprevalence was moderate in individuals under one year of age, despite the lack of detection of DENV-2 in primatophilic mosquitoes for up to three years prior, suggesting that non-primate hosts contributed to the maintenance of sylvatic DENV in this region.

American Samoa experienced multiple dengue outbreaks during 2008–2023. We employed a catalytic model to reconstruct historical dengue virus (DENV) transmission dynamics by estimating the annual force of infection (FOI) – or probability of DENV infection among susceptible individuals – during this period. We incorporated data from 661 dengue cases between 2016–2023 and two serosurveys. We also modeled the proportion of the population with 0, 1, or ≥2 previous infections to assess population risk. We estimated elevated FOIs during 2009 (11%; 95% CrI: 2%–38%), 2010 (15%; 95% CrI: 5%–29%), 2017 (50%; 95% CrI: 37%–67%), and 2018 (13%; 95% CrI 7%–24%). The proportion of the population with 0 previous infections was 22% in 2016, declined to 11% following the 2017–2018 outbreak, and rebounded to 20% in 2023. Our findings indicate a pattern of episodic dengue transmission in American Samoa, with substantial fluctuations in population immunity over time.

Background:The introduction of the wMel strain of Wolbachia into Aedes aegypti mosquitoes significantly reduces dengue virus transmission. We evaluated the impact of large-scale releases of Wolbachia-infected Ae. aegypti on dengue incidence in Campo Grande, a large urban city in the Central-West region of Brazil, in the first deployment of Wolbachia as an official dengue-control strategy by the Brazilian federal government. Methods:Mosquitoes infected with wMel Wolbachia were released in geographically phased deployments throughout Campo Grande from December 2020 through December 2023. An ovitrap surveillance network monitored Wolbachia prevalence in local Ae. aegypti populations during and after releases. Mixed-effects negative binomial regression was used to evaluate neighborhood-level monthly notified dengue incidence (2008-2024) as a function of monthly wMel exposure status, comparing fully treated (wMel prevalence stably ≥60%) and partially treated (ongoing releases or wMel <60%) with untreated periods, accounting for seasonal variation. Findings:More than 100 million Wolbachia-infected mosquitoes were released, achieving a post-intervention mean Wolbachia prevalence of 86.4% (95% CI 84.0-88.9), with 89% of intervention areas reaching stable Wolbachia levels ≥60%. Stable establishment of wMel at ≥60% prevalence was associated with a 63.2% (95% CI 51.9-71.9) reduction in dengue incidence. Interpretation:Our results demonstrate successful large-scale Wolbachia establishment in Ae. aegypti populations and a substantial epidemiological impact on dengue incidence in an urban Brazilian setting. This study provides robust evidence supporting Wolbachia deployment as an effective, sustainable public health intervention and validates its implementation as a federal government-supported dengue control strategy in Brazil. Funding:This work was supported by the Brazilian Ministry of Health and the Oswaldo Cruz Foundation.

BACKGROUND:There have been increasing numbers of travel-associated dengue cases reported but the true burden is unclear. Existing surveillance in non-endemic countries captures only a fraction of symptomatic cases in returning travelers due to underreporting. Therefore, we used mathematical modeling approaches to account for underreporting and estimate the number of dengue cases occurring during international travel. METHODOLOGY/PRINCIPAL FINDINGS:We obtained data on numbers of international air passengers from 43 non-endemic "origin" countries, risks of infection while in 119 dengue-endemic locations ("destinations"), and average durations of stay. We estimated travel-associated infections by multiplying the time spent by travelers in endemic countries by the risk of dengue infection and used data on reported cases to infer the fraction of cases that are included in surveillance systems. Our model estimated there were an average of 64,623 (95% CI: 25,068-138,283) symptomatic dengue cases ("cases") and 303,870 (95% CI: 292,841-315,240) total dengue infections (i.e., including symptomatic and asymptomatic infections) across 43 origin countries annually between 2010-19. The USA had the highest number of estimated cases followed by China. Among 34 origin countries that reported dengue cases, the fraction of cases reported varied widely (median 24.9%, range 2.5%-100%). The destination countries where most cases were infected were India, followed by Thailand. CONCLUSIONS/SIGNIFICANCE:We estimated a substantial burden of dengue among international air travelers from 43 non-endemic origin countries. The fraction of cases reported varied widely across origin countries and was also influenced by the specific origin-destination country pair examined.

Mobility data can help to reconstruct infectious disease dynamics and tailor control and elimination measures. We describe three challenges and opportunities to improve our understanding of human mobility for infectious disease research. We call for simulation and modelling, reporting guidelines and investment in data repositories.

BackgroundCluster randomized trials, which often enroll a small number of clusters, can benefit from constrained randomization, selecting a final randomization scheme from a set of known, balanced randomizations. Previous literature has addressed the suitability of adjusting the analysis for the covariates that were balanced in the design phase when the outcome is continuous or binary. Here we extended this work to time-to-event outcomes by comparing two model-based tests and a newly derived permutation test. A current cluster randomized trial of vector control for the prevention of mosquito-borne disease in children in Mexico is used as a motivating example.MethodsWe assessed type I error rates and power between simple randomization and constrained randomization using both prognostic and non-prognostic covariates via a simulation study. We compared the performance of a semi-parametric Cox proportional hazards model with robust variance, a mixed effects Cox model, and a permutation test utilizing deviance residuals.ResultsThe permutation test generally maintained nominal type I error-with the exception of the unadjusted analysis for constrained randomization-and also provided power comparable to the two Cox model-based tests. The model-based tests had inflated type I error when there were very few clusters per trial arm. All three methods performed well when there were 25 clusters per trial arm, as in the case of the motivating example.ConclusionFor time-to-event outcomes, covariate-constrained randomization was shown to improve power relative to simple randomization. The permutation test developed here was more robust to inflation of type I error compared to model-based tests. Gaining power by adjusting for covariates in the analysis phase was largely dependent on the number of clusters per trial arm.

Test-negative designs are increasingly used to evaluate vaccine effectiveness because of desirable properties like reduced confounding due to healthcare-seeking behaviors and lower cost compared to other study designs. An individual's decision to seek care often depends on their disease severity, with severe disease more likely to be captured than mild disease. As many vaccines likely attenuate disease severity, this phenomenon generally results in an upward-biased estimate of vaccine effectiveness against symptomatic disease. To address the resulting bias, analytic solutions like adjusting for or matching on severity have been suggested. In this paper, we examine the performance of the test-negative design under different vaccine effects on disease severity and the utility of adjusting or matching on severity. We further consider the implications of studies that focus only on milder disease by restricting recruitment to outpatient settings. Through an analytic framework and simulations accompanied by a real-world example, we demonstrate that, when vaccination attenuates disease severity, the magnitude of bias is influenced by the degree of under-ascertainment of mild disease relative to severe disease. When vaccination does not attenuate disease severity, bias is not present. We further show that analytic fixes negligibly impact bias and that outpatient-only studies frequently produce downward-biased estimates.

INTRODUCTION:Patient-centred task-shifting models may be a promising strategy in the community-based management of severe acute malnutrition (SAM) to alleviate pressure on health systems and increase access to treatment in low-resource settings. The engagement of caregivers in clinical and anthropometric surveillance has not been evaluated. OBJECTIVES:We examined the effect of caregiver training on their knowledge and confidence in at-home clinical and anthropometric surveillance of children with uncomplicated SAM in Sokoto, Nigeria. METHODS:We used data from a cross-over cluster-randomised trial (n clusters=10) comparing a monthly follow-up schedule with caregiver training to standard weekly follow-up for the outpatient management of children 6-59 months with uncomplicated SAM. Caregivers in the monthly follow-up group received a one-time training on at-home clinical surveillance and mid-upper arm circumference (MUAC) measurement. Intention-to-treat analyses assessed mean differences in knowledge and confidence scores within the monthly follow-up group and between groups at enrolment, post-training, programme discharge and 3 months post-discharge. Accuracy of MUAC measurement and classification was compared in the monthly follow-up group to study staff at enrolment post-training, programme discharge and 3 months post-discharge. RESULTS:Of 3945 enrolled children, 96% were followed to programme discharge and 91% to 3 months post-discharge. Caregivers' knowledge and confidence scores in clinical surveillance increased significantly in the monthly follow-up group post-training and remained elevated at programme discharge and 3 months post-discharge, compared with pretraining. Agreement in MUAC classification between caregiver and study staff was high (>92% agreement at all time points). Caregivers' knowledge and confidence scores in clinical surveillance were significantly greater in the monthly follow-up group compared with the weekly follow-up group at all time points. DISCUSSION:These findings confirm caregiver training increases knowledge and confidence in at-home clinical and anthropometric surveillance in the management of children with uncomplicated SAM, encouraging the continued consideration for task-shifting models in the community-based management of SAM in similar settings. TRIAL REGISTRATION NUMBER:NCT03140904.

BACKGROUND:Dengue is a substantial public health challenge in tropical regions, and is considered a global health threat owing to its expanding geographical range and increasing incidence as a result of climate change. Despite the availability of tetravalent dengue vaccines, real-world evidence on their effectiveness is scarce. We aimed to evaluate the vaccine effectiveness of the dengue vaccine TAK-003 in adolescents during the 2024 dengue outbreak in the state of São Paulo, Brazil. METHODS:This test-negative, case-control study was conducted among adolescents aged 10-14 years in São Paulo state, Brazil, from Feb 20 to Dec 31, 2024. Cases were defined as individuals with acute febrile illness and virologically confirmed dengue, and controls as individuals with acute febrile illness who tested negative for dengue; in both groups, confirmation was based on NS1 antigen or RT-PCR testing within 5 days of symptom onset. Data were obtained from the national surveillance databases for dengue and the São Paulo State Secretary of Health vaccination registry. We used mixed-effects logistic regression models to estimate vaccine effectiveness against symptomatic, virologically confirmed dengue and against hospitalisation with dengue after one or two doses of the vaccine. FINDINGS:Of 128 358 potentially eligible tests, 92 621 were included in the analysis: 43 873 from cases and 48 748 from controls. Adjusted vaccine effectiveness was 50·2% (95% CI 45·0-54·9) for the first dose and 61·7% (39·9-75·6) for the second dose against symptomatic dengue, and 67·5% (95% CI 43·4-81·3) for the first dose against hospitalisation with dengue. Protection against symptomatic disease began 14 days after the first dose (67·4% [57·2-75·1] at 14-27 days), but declined to 49·7% (30·4-63·6) after 90 days from the first dose. Sensitivity analyses showed the robustness of these findings, although estimates for the second dose were limited by the small number of events observed. INTERPRETATION:TAK-003 was effective against symptomatic dengue and hospitalisation with dengue in adolescents during a large outbreak caused predominantly by dengue virus serotypes 1 and 2. These findings underscore the importance of real-world evidence in guiding dengue vaccination strategies, particularly in high-transmission settings and during emergency response use. FUNDING:National Council for Scientific and Technological Development. TRANSLATION:For the Portuguese translation of the abstract see Supplementary Materials section.

OBJECTIVES:The SARS-CoV-2 BQ.1* variant rapidly spread globally in late 2022, posing a challenge due to its increased immune evasion.METHODS:We conducted a prevalence survey in Brazil from November 16 to December 22, 2022, as part of a cohort study. We conducted interviews and collected nasal samples for reverse transcription-polymerase chain reaction (RT-PCR) testing and whole-genome sequencing. Cumulative incidence was estimated using RT-PCR positivity, cycle threshold values, and external data on the dynamics of RT-PCR positivity following infection.RESULTS:Among 535 participants, 54% had documented SARS-CoV-2 exposure before this outbreak and 74% had received COVID-19 vaccination. In this study, 14.8% tested positive for SARS-CoV-2, with BQ.1* identified in 90.7% of cases. Using case data and cycle threshold values, cumulative incidence was estimated at 56% (95% confidence interval, 36-88%). Of the 79 positive participants, 48.1% had a symptomatic illness, with a lower proportion fulfilling the World Health Organization COVID-19 case definition compared to prior Omicron waves. No participants required medical attention.CONCLUSIONS:Despite high population-level hybrid immunity, the BQ.1* variant attacked 56% of our population. Lower disease severity was associated with BQ.1* compared to prior Omicron variants. Hybrid immunity may provide protection against future SARS-CoV-2 variants but in this case was not able to prevent widespread transmission.

We monitored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in Haiti from 2020 to 2023. Despite Haitian coronavirus disease 2019 (COVID-19) travel restrictions and in the setting of a vaccination rate of 2.7%, the timing and lineage evolution of the Haiti epidemic mirrored what was occurring in the rest of the world. Sources for importation of lineages into Haiti were the United States, the Dominican Republic, Europe, and Brazil, with exportation of lineages to the United States, the Dominican Republic, Europe, and Asia. Viral loads in patients infected by the Delta and Omicron BA.1 variants were correlated along the phylogenies, suggesting that higher viral loads have facilitated strain transmission and evolution.

Mobility data have been used to reconstruct infectious disease dynamics and tailor control and elimination measures. We describe three challenges in using these data and identify opportunities to leverage existing resources, improving our understanding of human mobility. We propose reporting guidelines to increase the interpretation, standardization, and reuse of existing mobility data sets.

Background The emergence of COVID-19 variants with immune scape and the waning of primary vaccine schemes effectiveness have prompted many countries to indicate fi rst and second booster COVID-19 vaccine doses to prevent severe COVID-19. However, current available evidence on second booster dose effectiveness are mostly limited to high-income countries, older adults, and mRNA-based vaccination schemes scenarios. We aimed to investigate the relative vaccine effectiveness (rVE) of the fourth dose compared to three doses for severe COVID-19 outcomes in Brazil; and compare the rVE of a fourth dose with an mRNA vaccine compared to adenovirus-based product in the same settings. Methods We performed a target emulated trial using a population-based cohort of individuals aged 40 years or older who have received a homologous primary scheme of CoronaVac, ChAdOx1, or BNT162b2, and any third dose product and were eligible for the fourth dose in Brazil. The primary outcome was COVID-19 associated hospitalization or death. We built Cohort A matching individuals vaccinated with a fourth dose to individuals who received three doses to estimate the rVE of the fourth dose. We built Cohort B, a subset of Cohort A, matching mRNA-based (mRNA) to adenovirus-based fourth dose vaccinated individuals to compare their relative hazards for severe COVID-19. Findings 46,693,484 individuals were included in Cohort A and 6,763,016 in Cohort B. 45% of them were aged between 40 and 60 years old, and 48% between 60 and 79 years old. In Cohort A, the most common previous series was a ChAdOx1 two-dose followed by BNT162b2 (44%), and a CoronaVac two-dose followed by a BNT162b2 (36%). Among those fourth dose vaccinated, 36.9% received ChAdOx1, 32.7% Ad26.COV2.S, 25.8% BNT162b2, and 4.7% CoronaVac. In Cohort B, among those who received an adenovirus fourth dose, 53.7% received ChAdOx1 and 46.3% received Ad26.COV2.S. The estimated rVE for the primary outcome of four doses compared to three doses was 44.1% (95% CI 42.3 - 46.0), with some waning during follow-up (rVE 7 - 60 days 46.8% [95% CI 44.4 - 49.1], rVE after 120 days 33.8% [95% CI 18.0 - 46.6]). Among fourth dose vaccinated individuals, mRNA-based vaccinated individuals had lower hazards for hospitalization or death compared to adenovirus-vaccinated individuals

The emergence of SARS-CoV-2 into a highly susceptible global population was primarily driven by human mobility-induced introduction events. Especially in the early stages, understanding mobility was vital to mitigating the pandemic prior to widespread vaccine availability. We conducted a systematic review of studies published from January 1, 2020, to May 9, 2021, that used population-level human mobility data to understand SARS-CoV-2 transmission. Of the 5505 papers with abstracts screened, 232 were included in the analysis. These papers focused on a range of specific questions but were dominated by analyses focusing on the USA and China. The majority included mobile phone data, followed by Google Community Mobility Reports, and few included any adjustments to account for potential biases in population sampling processes. There was no clear relationship between methods used to integrate mobility and SARS-CoV-2 data and goals of analysis. When considering papers focused only on the estimation of the effective reproductive number within the US, there was no clear relationship identified between this measure and changes in mobility patterns. Our findings underscore the need for standardized, systematic ways to identify the source of mobility data, select an appropriate approach to using it in analysis, and reporting.