Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones.

Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases

'A bite before bed': exposure to malaria vectors outside the times of net use in the highlands of western Kenya.

BACKGROUND: The human population in the highlands of Nyanza Province, western Kenya, is subject to sporadic epidemics of Plasmodium falciparum. Indoor residual spraying (IRS) and long-lasting insecticide treated nets (LLINs) are used widely in this area. These interventions are most effective when Anopheles rest and feed indoors and when biting occurs at times when individuals use LLINs. It is therefore important to test the current assumption of vector feeding preferences, and late night feeding times, in order to estimate the extent to which LLINs protect the inhabitants from vector bites. METHODS: Mosquito collections were made for six consecutive nights each month between June 2011 and May 2012. CDC light-traps were set next to occupied LLINs inside and outside randomly selected houses and emptied hourly. The net usage of residents, their hours of house entry and exit and times of sleeping were recorded and the individual hourly exposure to vectors indoors and outdoors was calculated. Using these data, the true protective efficacy of nets (P*), for this population was estimated, and compared between genders, age groups and from month to month. RESULTS: Primary vector species (Anopheles funestus s.l. and Anopheles arabiensis) were more likely to feed indoors but the secondary vector Anopheles coustani demonstrated exophagic behaviour (p < 0.05). A rise in vector biting activity was recorded at 19:30 outdoors and 18:30 indoors. Individuals using LLINs experienced a moderate reduction in their overall exposure to malaria vectors from 1.3 to 0.47 bites per night. The P* for the population over the study period was calculated as 51% and varied significantly with age and season (p < 0.01). CONCLUSIONS: In the present study, LLINs offered the local population partial protection against malaria vector bites. It is likely that P* would be estimated to be greater if the overall suppression of the local vector population due to widespread community net use could be taken into account. However, the overlap of early biting habit of vectors and human activity in this region indicates that additional methods of vector control are required to limit transmission. Regular surveillance of both vector behaviour and domestic human-behaviour patterns would assist the planning of future control interventions in this region

Factors associated with high heterogeneity of malaria at fine spatial scale in the Western Kenyan highlands.

BACKGROUND: The East African highlands are fringe regions between stable and unstable malaria transmission. What factors contribute to the heterogeneity of malaria exposure on different spatial scales within larger foci has not been extensively studied. In a comprehensive, community-based cross-sectional survey an attempt was made to identify factors that drive the macro- and micro epidemiology of malaria in a fringe region using parasitological and serological outcomes. METHODS: A large cross-sectional survey including 17,503 individuals was conducted across all age groups in a 100 km(2) area in the Western Kenyan highlands of Rachuonyo South district. Households were geo-located and prevalence of malaria parasites and malaria-specific antibodies were determined by PCR and ELISA. Household and individual risk-factors were recorded. Geographical characteristics of the study area were digitally derived using high-resolution satellite images. RESULTS: Malaria antibody prevalence strongly related to altitude (1350-1600 m, p < 0.001). A strong negative association with increasing altitude and PCR parasite prevalence was found. Parasite carriage was detected at all altitudes and in all age groups; 93.2 % (2481/2663) of malaria infections were apparently asymptomatic. Malaria parasite prevalence was associated with age, bed net use, house construction features, altitude and topographical wetness index. Antibody prevalence was associated with all these factors and distance to the nearest water body. CONCLUSION: Altitude was a major driver of malaria transmission in this study area, even across narrow altitude bands. The large proportion of asymptomatic parasite carriers at all altitudes and the age-dependent acquisition of malaria antibodies indicate stable malaria transmission; the strong correlation between current parasite carriage and serological markers of malaria exposure indicate temporal stability of spatially heterogeneous transmission

The Impact of Hotspot-Targeted Interventions on Malaria Transmission in Rachuonyo South District in the Western Kenyan Highlands: A Cluster-Randomized Controlled Trial.

BACKGROUND: Malaria transmission is highly heterogeneous, generating malaria hotspots that can fuel malaria transmission across a wider area. Targeting hotspots may represent an efficacious strategy for reducing malaria transmission. We determined the impact of interventions targeted to serologically defined malaria hotspots on malaria transmission both inside hotspots and in surrounding communities. METHODS AND FINDINGS: Twenty-seven serologically defined malaria hotspots were detected in a survey conducted from 24 June to 31 July 2011 that included 17,503 individuals from 3,213 compounds in a 100-km2 area in Rachuonyo South District, Kenya. In a cluster-randomized trial from 22 March to 15 April 2012, we randomly allocated five clusters to hotspot-targeted interventions with larviciding, distribution of long-lasting insecticide-treated nets, indoor residual spraying, and focal mass drug administration (2,082 individuals in 432 compounds); five control clusters received malaria control following Kenyan national policy (2,468 individuals in 512 compounds). Our primary outcome measure was parasite prevalence in evaluation zones up to 500 m outside hotspots, determined by nested PCR (nPCR) at baseline and 8 wk (16 June-6 July 2012) and 16 wk (21 August-10 September 2012) post-intervention by technicians blinded to the intervention arm. Secondary outcome measures were parasite prevalence inside hotpots, parasite prevalence in the evaluation zone as a function of distance from the hotspot boundary, Anopheles mosquito density, mosquito breeding site productivity, malaria incidence by passive case detection, and the safety and acceptability of the interventions. Intervention coverage exceeded 87% for all interventions. Hotspot-targeted interventions did not result in a change in nPCR parasite prevalence outside hotspot boundaries (p ≥ 0.187). We observed an average reduction in nPCR parasite prevalence of 10.2% (95% CI -1.3 to 21.7%) inside hotspots 8 wk post-intervention that was statistically significant after adjustment for covariates (p = 0.024), but not 16 wk post-intervention (p = 0.265). We observed no statistically significant trend in the effect of the intervention on nPCR parasite prevalence in the evaluation zone in relation to distance from the hotspot boundary 8 wk (p = 0.27) or 16 wk post-intervention (p = 0.75). Thirty-six patients with clinical malaria confirmed by rapid diagnostic test could be located to intervention or control clusters, with no apparent difference between the study arms. In intervention clusters we caught an average of 1.14 female anophelines inside hotspots and 0.47 in evaluation zones; in control clusters we caught an average of 0.90 female anophelines inside hotspots and 0.50 in evaluation zones, with no apparent difference between study arms. Our trial was not powered to detect subtle effects of hotspot-targeted interventions nor designed to detect effects of interventions over multiple transmission seasons. CONCLUSIONS: Despite high coverage, the impact of interventions targeting malaria vectors and human infections on nPCR parasite prevalence was modest, transient, and restricted to the targeted hotspot areas. Our findings suggest that transmission may not primarily occur from hotspots to the surrounding areas and that areas with highly heterogeneous but widespread malaria transmission may currently benefit most from an untargeted community-wide approach. Hotspot-targeted approaches may have more validity in settings where human settlement is more nuclear. TRIAL REGISTRATION: ClinicalTrials.gov NCT01575613

Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones

Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases

Rotavirus Genotypes in Hospitalized Children With Acute Gastroenteritis Before and After Rotavirus Vaccine Introduction in Blantyre, Malawi, 1997-2019

BACKGROUND: Rotavirus vaccine (Rotarix [RV1]) has reduced diarrhea-associated hospitalizations and deaths in Malawi. We examined the trends in circulating rotavirus genotypes in Malawi over a 22-year period to assess the impact of RV1 introduction on strain distribution. METHODS: Data on rotavirus-positive stool specimens among children aged <5 years hospitalized with diarrhea in Blantyre, Malawi before (July 1997-October 2012, n = 1765) and after (November 2012-October 2019, n = 934) RV1 introduction were analyzed. Rotavirus G and P genotypes were assigned using reverse-transcription polymerase chain reaction. RESULTS: A rich rotavirus strain diversity circulated throughout the 22-year period; Shannon (H') and Simpson diversity (D') indices did not differ between the pre- and postvaccine periods (H' P < .149; D' P < .287). Overall, G1 (n = 268/924 [28.7%]), G2 (n = 308/924 [33.0%]), G3 (n = 72/924 [7.7%]), and G12 (n = 109/924 [11.8%]) were the most prevalent genotypes identified following RV1 introduction. The prevalence of G1P[8] and G2P[4] genotypes declined each successive year following RV1 introduction, and were not detected after 2018. Genotype G3 reemerged and became the predominant genotype from 2017 onward. No evidence of genotype selection was observed 7 years post-RV1 introduction. CONCLUSIONS: Rotavirus strain diversity and genotype variation in Malawi are likely driven by natural mechanisms rather than vaccine pressure

Comparative whole genome analysis reveals re-emergence of human Wa-like and DS-1-like G3 rotaviruses after Rotarix vaccine introduction in Malawi

G3 rotaviruses rank among the most common rotavirus strains worldwide in humans and animals. However, despite a robust long-term rotavirus surveillance system from 1997 at Queen Elizabeth Central Hospital in Blantyre, Malawi, these strains were only detected from 1997 to 1999 and then disappeared and re-emerged in 2017, five years after the introduction of the Rotarix rotavirus vaccine. Here we analysed representative 27 whole genome sequences (G3P[4], n=20; G3P[6], n=1; and G3P[8], n=6) randomly selected each month between November 2017 and August 2019 to understand how G3 strains re-emerged in Malawi. We found four genotype constellations that were associated with the emergent G3 strains and co-circulated in Malawi post-Rotarix vaccine introduction: G3P[4] and G3P[6] strains with the DS-1-like genetic backbone genes (G3-P[4]-I2-R2-C2-M2-A2-N2-T2-E2-H2) and G3-P[6]-I2-R2-C2-M2-A2-N2-T2-E2-H2), G3P[8] strains with the Wa-like genetic backbone genes (G3-P[8]-I1-R1-C1-M1-A1-N1-T1-E1-H1), and reassortant G3P[4] strains consisting of the DS-1-like genetic backbone genes and a Wa-like NSP2 (N1) gene (G3-P[4]-I2-R2-C2-M2-A2-N1-T2-E2-H2). Time-resolved phylogenetic trees demonstrated that the most recent common ancestor for each RNA segment of the emergent G3 strains was between 1996 and 2012, possibly through introductions from outside the country due to the limited genetic similarity with G3 strains which circulated before their disappearance in the late 1990s. Further genomic analysis revealed that the reassortant DS-1-like G3P[4] strains acquired a Wa-like NSP2 genome segment (N1 genotype) through intergenogroup reassortment; an artiodactyl-like VP3 through intergenogroup interspecies reassortment; and VP6, NSP1 and NSP4 segments through intragenogroup reassortment likely before importation into Malawi. Additionally, the emergent G3 strains contain amino acid substitutions within the antigenic regions of the VP4 proteins which could potentially impact the binding of rotavirus vaccine-induced antibodies. Altogether, our findings show that multiple strains with either Wa-like or DS-1-like genotype constellations have driven the re-emergence of G3 strains. The findings also highlight the role of human mobility and genome reassortment events in the cross-border dissemination and evolution of rotavirus strains in Malawi necessitating the need for long-term genomic surveillance of rotavirus in high disease burden settings to inform disease prevention and control

Development of an amplicon-based sequencing approach in response to the global emergence of mpox

The 2022 multicountry mpox outbreak concurrent with the ongoing Coronavirus Disease 2019 (COVID-19) pandemic further highlighted the need for genomic surveillance and rapid pathogen whole-genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical specimens that tested presumptively positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (Ct) (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR Ct below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon-based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole-genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.This publication was made possible by CTSA Grant Number UL1 TR001863 from the National Center for Advancing Translational Science (NCATS), a component of the National Institutes of Health (NIH) awarded to CBFV. INSA was partially funded by the HERA project (Grant/ 2021/PHF/23776) supported by the European Commission through the European Centre for Disease Control (to VB).info:eu-repo/semantics/publishedVersio