Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.
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ABSTRACT:
SUBMITTER: Ramiadantsoa T
PROVIDER: S-EPMC8351785 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.
| S-EPMC8641444 | biostudies-literature
Project description:Modelling disease dynamics is most useful when data are limited. We present a spatial transmission model for the spread of canine rabies in the currently rabies-free wild dog population of Australia. The introduction of a sub-clinically infected dog from Indonesia is a distinct possibility, as is the spillover infection of wild dogs. Ranges for parameters were estimated from the literature and expert opinion, or set to span an order of magnitude. Rabies was judged to have spread spatially if a new infectious case appeared 120 km from the index case. We found 21% of initial value settings resulted in canine rabies spreading 120km, and on doing so at a median speed of 67 km/year. Parameters governing dog movements and behaviour, around which there is a paucity of knowledge, explained most of the variance in model outcomes. Dog density, especially when interactions with other parameters were included, explained some of the variance in whether rabies spread 120km, but dog demography (mean lifespan and mean replacement period) had minimal impact. These results provide a clear research direction if Australia is to improve its preparedness for rabies.
| S-EPMC5289603 | biostudies-literature
Project description:There are a huge number of pathogens with multi-component transmission cycles, involving amplifier hosts, vectors or complex pathogen life cycles. These complex systems present challenges in terms of modeling and policy development. A lethal tick-borne infectious disease, the Brazilian Spotted Fever (BSF), is a relevant example of that. The current increase of human cases of BSF has been associated with the presence and expansion of the capybara Hydrochoerus hydrochaeris, amplifier host for the agent Rickettsia rickettsii and primary host for the tick vector Amblyomma sculptum. We introduce a stochastic dynamical model that captures the spatial distribution of capybaras and ticks to gain a better understanding of the spatial spread of the R. rickettsii and potentially predict future epidemic outcomes. We implemented a reaction-diffusion process in which individuals were divided into classes denoting their state with respect to the disease. The model considered bidirectional movements between base and destination locations limited by the carrying capacity of the environment. We performed systematic stochastic simulations and numerical analysis of the model and investigate the impact of potential interventions to mitigate the spatial spread of the disease. The mobility of capybaras and their attached ticks was significantly influenced by the birth rate of capybaras and therefore, disease propagation velocity was higher in places with higher carrying capacity. Some geographical barriers, generated for example by riparian reforesting, can impede the spatial spread of BSF. The results of this work will allow the formulation of public actions focused on the prevention of BSF human cases.
| S-EPMC6324817 | biostudies-literature
Project description:COVID-19 constitutes the largest pandemic in the last 100 years. In view of the rapid spread of the virus, it is necessary to study the sociodemographic characteristics, hygiene habits, activity and mobility, and comorbidities of SARS-CoV-2 infection to be able to implement prevention strategies. For this purpose, a survey including the variables of interest was designed to try to understand the exponential spread of the virus despite the implemented severe restrictive mobility measures during the period of maximum confinement in Spain. This study conducted throughout the Spanish territory aims to clarify other routes of transmission of the COVID-19 during confinement, risk factors, and the effectiveness of the recommended hygiene measures to detect critical points of exposure to the virus and thus reduce its spread in this and possible future pandemics that could compromise public health. Our results show that living with a COVID-19 patient increased the risk of contagion by 60 times. Among all the sociodemographic variables analyzed, walking the dog have shown to have the strongest effect by increasing the risk by 78%. The most effective hygiene measure reducing the prevalence of the disease was the disinfection of products purchased from the market upon arrival home (which reduced the risk by 94%), above other hygiene measures, such as wearing masks, gloves, ethanol disinfection, bleaching and others. The mobility variable studied that showed the largest increase in the prevalence of the disease was working on site at the workplace (increased the risk by 76%). A significant higher prevalence of the disease was also detected among respondents who used the modality of acquiring basic commodities using home delivery service compared to those who chose in-store shopping.
| S-EPMC7505892 | biostudies-literature
Project description: Not available
| S-BSST379 | biostudies-other
Project description:Timely, accurate, and comparative data on human mobility is of paramount importance for epidemic preparedness and response, but generally not available or easily accessible. Mobile phone metadata, typically in the form of Call Detail Records (CDRs), represents a powerful source of information on human movements at an unprecedented scale. In this work, we investigate the potential benefits of harnessing aggregated CDR-derived mobility to predict the 2015-2016 Zika virus (ZIKV) outbreak in Colombia, when compared to other traditional data sources. To simulate the spread of ZIKV at sub-national level in Colombia, we employ a stochastic metapopulation epidemic model for vector-borne diseases. Our model integrates detailed data on the key drivers of ZIKV spread, including the spatial heterogeneity of the mosquito abundance, and the exposure of the population to the virus due to environmental and socio-economic factors. Given the same modelling settings (i.e. initial conditions and epidemiological parameters), we perform in-silico simulations for each mobility network and assess their ability in reproducing the local outbreak as reported by the official surveillance data. We assess the performance of our epidemic modelling approach in capturing the ZIKV outbreak both nationally and sub-nationally. Our model estimates are strongly correlated with the surveillance data at the country level (Pearson's r = 0.92 for the CDR-informed network). Moreover, we found strong performance of the model estimates generated by the CDR-informed mobility networks in reproducing the local outbreak observed at the sub-national level. Compared to the CDR-informed networks, the performance of the other mobility networks is either comparatively similar or substantially lower, with no added value in predicting the local epidemic. This suggests that mobile phone data captures a better picture of human mobility patterns. This work contributes to the ongoing discussion on the value of aggregated mobility estimates from CDRs data that, with appropriate data protection and privacy safeguards, can be used for social impact applications and humanitarian action.
| S-EPMC9299334 | biostudies-literature
Project description:Emerging infectious diseases can have devastating effects on host communities, causing population collapse and species extinctions. The timing of novel pathogen arrival into naïve species communities can have consequential effects that shape the trajectory of epidemics through populations. Pathogen introductions are often presumed to occur when hosts are highly mobile. However, spread patterns can be influenced by a multitude of other factors including host body condition and infectiousness. White-nose syndrome (WNS) is a seasonal emerging infectious disease of bats, which is caused by the fungal pathogen Pseudogymnoascus destructans. Within-site transmission of P. destructans primarily occurs over winter; however, the influence of bat mobility and infectiousness on the seasonal timing of pathogen spread to new populations is unknown. We combined data on host population dynamics and pathogen transmission from 22 bat communities to investigate the timing of pathogen arrival and the consequences of varying pathogen arrival times on disease impacts. We found that midwinter arrival of the fungus predominated spread patterns, suggesting that bats were most likely to spread P. destructans when they are highly infectious, but have reduced mobility. In communities where P. destructans was detected in early winter, one species suffered higher fungal burdens and experienced more severe declines than at sites where the pathogen was detected later in the winter, suggesting that the timing of pathogen introduction had consequential effects for some bat communities. We also found evidence of source-sink population dynamics over winter, suggesting some movement among sites occurs during hibernation, even though bats at northern latitudes were thought to be fairly immobile during this period. Winter emergence behaviour symptomatic of white-nose syndrome may further exacerbate these winter bat movements to uninfected areas. Our results suggest that low infectiousness during host migration may have reduced the rate of expansion of this deadly pathogen, and that elevated infectiousness during winter plays a key role in seasonal transmission. Furthermore, our results highlight the importance of both accurate estimation of the timing of pathogen spread and the consequences of varying arrival times to prevent and mitigate the effects of infectious diseases.
| S-EPMC8248334 | biostudies-literature
Project description:BackgroundAlthough an increasing body of data reports the detection of SARS-CoV-2 RNA in air, this does not correlate to the presence of infectious viruses, thus not evaluating the risk for airborne COVID-19. Hence there is a marked knowledge gap that requires urgent attention. Therefore, in this systematic review, viability/stability of airborne SARS-CoV-2, SARS-CoV and MERS-CoV viruses is discussed.MethodsA systematic literature review was performed on PubMed/MEDLINE, Web of Science and Scopus to assess the stability and viability of SARS-CoV, MERS-CoV and SARS-CoV-2 on air samples.Results and discussionThe initial search identified 27 articles. Following screening of titles and abstracts and removing duplicates, 11 articles were considered relevant. Temperatures ranging from 20 °C to 25 °C and relative humidity ranging from 40% to 50% were reported to have a protective effect on viral viability for airborne SARS-CoV and MERS-CoV. As no data is yet available on the conditions influencing viability for airborne SARS-CoV-2, and given the genetic similarity to SARS-CoV and MERS-CoV, one could extrapolate that the same conditions would apply. Nonetheless, the effect of these conditions seems to be residual considering the increasing number of cases in the south of USA, Brazil and India, where high temperatures and humidities have been observed.ConclusionHigher temperatures and high relative humidity can have a modest effect on SARS-CoV-2 viability in the environment, as reported in previous studies to this date. However, these studies are experimental, and do not support the fact that the virus has efficiently spread in the tropical regions of the globe, with other transmission routes such as the contact and droplet ones probably being responsible for the majority of cases reported in these regions, along with other factors such as human mobility patterns and contact rates. Further studies are needed to investigate the extent of aerosol transmission of SARS-CoV-2 as this would have important implications for public health and infection-control policies.
| S-EPMC7543729 | biostudies-literature
Project description:The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing coronavirus disease-2019 (COVID-19) likely has evolutionary origins in other animals than humans based on genetically related viruses existing in rhinolophid bats and pangolins. Similar to other animal coronaviruses, SARS-CoV-2 contains a functional furin cleavage site in its spike protein, which may broaden the SARS-CoV-2 host range and affect pathogenesis. Whether ongoing zoonotic infections are possible in addition to efficient human-to-human transmission remains unclear. In contrast, human-to-animal transmission can occur based on evidence provided from natural and experimental settings. Carnivores, including domestic cats, ferrets and minks, appear to be particularly susceptible to SARS-CoV-2 in contrast to poultry and other animals reared as livestock such as cattle and swine. Epidemiologic evidence supported by genomic sequencing corroborated mink-to-human transmission events in farm settings. Airborne transmission of SARS-CoV-2 between experimentally infected cats additionally substantiates the possibility of cat-to-human transmission. To evaluate the COVID-19 risk represented by domestic and farmed carnivores, experimental assessments should include surveillance and health assessment of domestic and farmed carnivores, characterization of the immune interplay between SARS-CoV-2 and carnivore coronaviruses, determination of the SARS-CoV-2 host range beyond carnivores and identification of human risk groups such as veterinarians and farm workers. Strategies to mitigate the risk of zoonotic SARS-CoV-2 infections may have to be developed in a One Health framework and non-pharmaceutical interventions may have to consider free-roaming animals and the animal farming industry.
| S-EPMC7675418 | biostudies-literature
Project description:BACKGROUND:During the current worldwide pandemic, coronavirus disease 2019 (Covid-19) was first diagnosed in Iceland at the end of February. However, data are limited on how SARS-CoV-2, the virus that causes Covid-19, enters and spreads in a population. METHODS:We targeted testing to persons living in Iceland who were at high risk for infection (mainly those who were symptomatic, had recently traveled to high-risk countries, or had contact with infected persons). We also carried out population screening using two strategies: issuing an open invitation to 10,797 persons and sending random invitations to 2283 persons. We sequenced SARS-CoV-2 from 643 samples. RESULTS:As of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for targeted testing had positive results for infection with SARS-CoV-2. Of those tested in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%) in the random-population screening tested positive for the virus. In total, 6% of the population was screened. Most persons in the targeted-testing group who received positive tests early in the study had recently traveled internationally, in contrast to those who tested positive later in the study. Children under 10 years of age were less likely to receive a positive result than were persons 10 years of age or older, with percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population screening, no child under 10 years of age had a positive result, as compared with 0.8% of those 10 years of age or older. Fewer females than males received positive results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6% vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and changed over time. The percentage of infected participants that was determined through population screening remained stable for the 20-day duration of screening. CONCLUSIONS:In a population-based study in Iceland, children under 10 years of age and females had a lower incidence of SARS-CoV-2 infection than adolescents or adults and males. The proportion of infected persons identified through population screening did not change substantially during the screening period, which was consistent with a beneficial effect of containment efforts. (Funded by deCODE Genetics-Amgen.).
| S-EPMC7175425 | biostudies-literature