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Background Blood smear microscopy remains the gold-standard method to diagnose and quantify malaria parasite density. In addition, parasite genotyping of select loci is the most utilized method for distinguishing recrudescent and new infections and to determine the number of strains per sample. In research settings, blood may be obtained from capillary or venous compartments, and results from these matrices have been used interchangeably. Our aim was to compare quantitative results for parasite density and strain complexity from both compartments. Methods In a prospective observational study, children and adults presenting with uncomplicated Plasmodium falciparum malaria, simultaneous capillary and venous blood smears and dried blood spots were collected over 42-days following treatment with artemether-lumefantrine. Blood smears were read by two microscopists, any discrepancies resolved by a third reader. Parasite DNA fingerprinting was conducted using six microsatellites. Bland Altman analysis and paired t-test/McNemar’s test were used to assess the difference in density readings and measurements. Results Two hundred twenty-three participants were included in the analysis (177 children (35 HIV-infected/142 HIV-uninfected), 21 HIV-uninfected pregnant women, and 25 HIV-uninfected non-pregnant adults). Parasite density measurements did not statistically differ between capillary and venous blood smears at the time of presentation, nor over the course of 42-day follow-up. Characterization of merozoite surface protein-2 (MSP-2) genetic polymorphism demonstrated a higher level of strain diversity at the time of presentation in venous samples, as compared with capillary specimens ( p = 0.02). There was a high degree of variability in genotype-corrected outcomes when pairs of samples from each compartment were compared using MSP-2 alone, although the variability was reduced with the use of multiple markers. Conclusions Parasite density measurements do not statistically differ between capillary and venous compartments in all studied demographic groups at the time of presentation with malaria, or over the course of follow-up. More strains were detected by MSP-2 genotyping in venous samples than in capillary samples at the time of malaria diagnosis. The use of multiple polymorphic markers reduces the impact of variability in strain detection on genotype-corrected outcomes. This study confirms that both capillary and venous compartments can be used for sampling with confidence in the clinical research setting. Trial registration The trial was registered at ClinicalTrials.gov under registration no. NCT01717885 . Electronic supplementary material The online version of this article (10.1186/s12879-019-4174-1) contains supplementary material, which is available to authorized users.

In the United States, tick-borne diseases are increasing in incidence and cases are reported over an expanding geographical area. Avoiding tick bites is a key strategy in tick-borne disease prevention, and this requires current and accurate information on where humans are at risk for exposure to ticks. Based on a review of published literature and records in the U.S. National Tick Collection and National Ecological Observatory Network databases, we compiled an updated county-level map showing the reported distribution of the American dog tick, Dermacentor variabilis (Say). We show that this vector of the bacterial agents causing Rocky Mountain spotted fever and tularemia is widely distributed, with records derived from 45 states across the contiguous United States. However, within these states, county-level records of established tick populations are limited. Relative to the range of suitable habitat for this tick, our data imply that D. variabilis is currently underreported in the peer-reviewed literature, highlighting a need for improved surveillance and documentation of existing tick records.

Colorado instituted stay-at-home orders to reduce community transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). To inform public health messaging and measures that could be used after reopening, persons with laboratory-confirmed COVID-19 during March 9-26 from nine Colorado counties comprising approximately 80% of the state's population † (Adams, Arapahoe, Boulder, Denver, Douglas, El Paso, Jefferson, Larimer, and Weld) were asked about possible exposures to SARS-CoV-2 before implementation of stay-at-home orders. Among 1,738 persons meeting the inclusion criteria § in the Colorado Electronic Disease Surveillance System, 600 were randomly selected and interviewed using a standardized questionnaire by telephone. Data collection during April 10-30 included information about demographic characteristics, occupations, and selected activities in the 2 weeks preceding symptom onset. During the period examined, SARS-CoV-2 molecular testing was widely available in Colorado; community transmission was documented before implementation of the stay-at-home order. At least three attempts were made to contact all selected patients or their proxy (for deceased patients, minors, and persons unable to be interviewed [e.g., those with dementia]) on at least 2 separate days, at different times of day. Data were entered into a Research Electronic Data Capture (version 9.5.13; Vanderbilt University) database, and descriptive analyses used R statistical software (version 3.6.3; The R Foundation). Among the 600 randomly selected COVID-19 patients, 133 (22%) were unreachable, 57 (10%) declined to participate, and 46 (8%) were ineligible (e.g., the onset date was too early or the patient was asymptomatic), leaving 364 (61%) participants. The median age of participants was 50 years (interquartile range = 34-64 years), and 187 (51%) were male. Overall, 206 (57%) participants identified as non-Hispanic white and 75 (21%) as Hispanic. Among all participants, 345 (95%) reported having health insurance, 128 (35%) were hospitalized and 18 (5%) died. Occupations reported by the 264 (73%) * These authors contributed equally. † https://demography.dola.colorado.gov/population/population-totals-counties/. § Inclusion criteria consisted of laboratory-confirmed SARS-CoV-2 infection, presence of ≥1 symptom to establish illness onset date, and known hospitalization status.