Most downloaded biology preprints, all time
in category health policy
361 results found. For more information, click each entry to expand.
882 downloads medRxiv health policy
Mobility control measures are of crucial importance for public health planning in combating the COVID-19 pandemic. Previous studies established the impact of population outflow from Wuhan on the spatial spread of coronavirus in China and hinted the impact of the other three mobility patterns, i.e., population outflow from Hubei province excluding Wuhan, population inflow from cities outside Hubei, and intra-city population movement. However, the overall impact of all mobility patterns, or the impact of the different timing of mobility restriction intervention, are not systematically analyzed. Here we apply the cumulative confirmed cases and mobility data of 350 Chinese cities outside Hubei to explore the relationships between all mobility patterns and epidemic spread, and estimate the impact of local travel restrictions, both in terms of level and timing, on the epidemic control based on mobility change. The relationships were identified by using Pearson correlation analysis and stepwise multivariable linear regression, while scenario simulation was used to estimate the mobility change caused by local travel restrictions. Our analysis shows that: (1) all mobility patterns correlated with the spread of the coronavirus in Chinese cities outside Hubei, while the corrleations droppd with the implemetation of travel restrictions; (2) the cumulative confirmed cases in two weeks after the Wuhan lockdown was mainly brought by three patterns of inter-city population movement, while those in the third and fourth weeks after was significantly influenced by the number of intra-city population movement; (3) the local travel restrictions imposed by cities outside Hubei have averted 1,960 (95%PI: 1,474-2,447) more infections, taking 22.4% (95%PI: 16.8%-27.9%) of confirmed ones, in two weeks after the Wuhan lockdown, while more synchronized implementation would further decrease the number of confirmed cases in the same period by 15.7% (95%PI:15.4%-16.0%) or 1,378 (95%PI: 1,353-1,402) cases; and (4) local travel restrictions on different mobility patterns have different degrees of protection on cities with or without initial confirmed cases until the Wuhan lockdown. Our results prove the effectiveness of local travel restrictions and highlight the importance of synchronized implementation of mobility control across cities in mitigating the COVID-19 transmission.
855 downloads medRxiv health policy
In response to the SARS-CoV-2 pandemic, the Austrian governmental crisis unit commissioned a forecast consortium with regularly projections of case numbers and demand for hospital beds. The goal was to assess how likely Austrian ICUs would become overburdened with COVID-19 patients in the upcoming weeks. We consolidated the output of three independent epidemiological models (ranging from agent-based micro simulation to parsimonious compartmental models) and published weekly short-term forecasts for the number of confirmed cases as well as estimates and upper bounds for the required hospital beds. Here, we report on three key contributions by which our forecasting and reporting system has helped shaping Austria's policy to navigate the crisis, namely (i) when and where case numbers and bed occupancy are expected to peak during multiple waves, (ii) whether to ease or strengthen non-pharmaceutical intervention in response to changing incidences, and (iii) how to provide hospital managers guidance to plan health-care capacities. Complex mathematical epidemiological models play an important role in guiding governmental responses during pandemic crises, in particular when they are used as a monitoring system to detect epidemiological change points.
811 downloads medRxiv health policy
Background To combat the Covid-19 pandemic in the United States, many states and Washington DC enacted Stay-at-Home order and nonpharmaceutical mitigation interventions. This study examined the determinants of the timing to implement an intervention. Through an impact analysis, the study explored the effects of the interventions and the potential risks of removing them under the context of reopening the economy. Method A content analysis identified nine types of mitigation interventions and the timing at which states enacted these strategies. A proportional hazard model, a multiple-event survival model, and a random-effect spatial error panel model in conjunction with a robust method analyzing zero-inflated and skewed outcomes were employed in the data analysis. Findings To our knowledge, we provided in this article the first explicit analysis of the timing, determinants, and impacts of mitigation interventions for all states and Washington DC in the United States during the first five weeks of the pandemic. Unlike other studies that evaluate the Stay-at-Home order by using simulated data, the current study employed the real data of various case counts of Covid-19. The study obtained two meritorious findings: (1) states with a higher prevalence of Covid-19 cases per 10,000 population reacted more slowly to the outbreak, suggesting that some states may have missed the optimal timing to prevent the wide spread of the Covid-19 disease; and (2) of nine mitigation measures, three (non-essential business closure, large-gathering bans, and restaurant/bar limitations) showed positive impacts on reducing cumulative cases, new cases, and death rates across states. Interpretation The opposite direction of the prevalence rate on the timing of issuing the mitigation interventions partially explains why the Covid-19 caseload in the U.S. remains high. A swift implementation of social distancing is crucial-the key is not whether such measures should be taken but when. Because there is no preventive vaccine and because there are few potentially effective treatments, recent reductions in new cases and deaths must be due, in large part, to the social interventions delivered by states. The study suggests that the policy of reopening economy needs to be implemented carefully.
808 downloads medRxiv health policy
By the end of February 2021, when 48% of the Israeli population was immune, the number of new positive COVID-19 cases significantly dropped across all ages. Understanding which parameters influenced this drop and how to minimize the number of hospitalizations and overall positive cases is urgently needed. In this study we conducted an observational analysis which included COVID-19 data with over 12,000,000 PCR tests from 250 cities in Israel. In addition, we performed a simulation of different vaccination campaigns to find the optimal policy. Our analysis revealed that cities with younger populations reached a decrease in new cases when a lower percentage of their residents were immunized, showing that median age is a crucial parameter effecting overall immunity, while other parameters appeared to be insignificant. This variance between cities is explained by recalculating the immunized population and multiplying each individual by a factor symbolizing the impact of their age on the spread on the virus. This factor is easily calculated from historical data of positive cases per age. The simulation proves that prioritizing different age groups or changing the rate of vaccinations drastically effects the overall hospitalizations and positive cases.
808 downloads medRxiv health policy
Background. The added value of interventions to prevent the transmission of SARS-CoV-2 among university affiliates is uncertain but needed as universities attempt to remain open. Methods. We use a decision-analytic simulation to examine the cost-effectiveness of common interventions to reduce SARS-CoV-2 transmission. We use Columbia University for reference values but our approach centers around an online model that allows users to tailor the model and interventions to their local conditions and existing strategies. All interventions are compared relative to implementing the Centers for Disease Control and Prevention (CDC) guidelines alone. Results. At prevalence rate of actively infectious cases of COVID-19 in the community surrounding the university of 0.1%, using a symptom-checking mobile application is cost-saving relative to CDC guidelines alone and the university can expect to remain open. At a prevalence of 1%, standardizing masks will be cost-saving. At a prevalence rate of 2%, thermal imaging cameras cost $965,070 (95% credible interval [CrI] = $198,821, $2.15 million)/quality-adjusted life year (QALY) gained. One-time testing on entry costs $1.08 million (95% CrI = $170,703, $3.33 million)/QALY gained. Weekly testing costs $820,119 (95% CrI = $452,673, $1.68 million)/QALY gained. Upgrades to ventilation systems or installation of far-ultraviolet C lighting systems will be cost-effective at a willingness-to-pay threshold of $200,000/QALY gained only if aerosols account for 86-90% of all on-campus transmission of SARS-CoV-2. Conclusions. The value of interventions to prevent transmission of SARS-CoV-2 vary greatly with the prevalence rate of actively infectious cases of COVID-19 in the community surrounding the university.
794 downloads medRxiv health policy
BackgroundCoronavirus disease-19 (COVID-19) is a global pandemic, with the potential to infect nearly 60% of the population. The anticipated spread of the virus requires an urgent appraisal of the capacity of US healthcare services and the identification of states most vulnerable to exceeding their capacity MethodsIn the American Hospital Association survey for 2018, a database of US community hospitals, we identified total inpatient beds, adult intensive care unit (ICU) beds, and airborne isolation rooms across all hospitals in each state of continental US. The burden of COVID-19 hospitalizations was estimated based on a median hospitalization duration of 12 days and was evaluated for a 30-day reporting period. ResultsAt 5155 US community hospitals across 48 states in the contiguous US and Washington DC, there were a total of 788,032 inpatient beds, 68,280 adult ICU beds, and 44,222 isolation rooms. The median daily bed occupancy was 62.8% (IQR 58.1%, 66.6%) across states. Nationally, for every 10,000 individuals, there are 24.2 inpatient beds, 2.8 adult ICU beds, and 1.4 isolation beds. There is a 3-fold variation in the number of inpatient beds available across the US, ranging from 16.4 per 10,000 in Oregon to 47 per 10,000 in South Dakota. There was also a similar 3-fold variation in available or non-occupied beds, ranging from 4.7 per 10,000 in Connecticut through 18.3 per 10,000 in North Dakota. The availability of ICU beds is low nationally, ranging from 1.4 per 10,000 in Nevada to 4.7 per 10000 in Washington DC. Hospitalizations for COVID-19 in a median 0.2% (IQR 0.2 %, 0.3%) of state population, or 1.4% of states older adults (1.0%, 1.9%) will require all non-occupied beds. Further, a median 0.6% (0.5%, 0.8%) of state population, or 3.9% (3.1%, 4.6%) of older individuals would require 100% of inpatient beds. ConclusionThe COVID-19 pandemic is likely to overwhelm the limited number of inpatient and ICU beds for the US population. Hospitals in half of US states would exceed capacity if less than 0.2% of the state population requires hospitalization in any given month.
789 downloads medRxiv health policy
Background: Coronavirus disease 2019 (COVID-19) is an international emergency that has been addressed in many countries by changes in and restrictions on behaviour. These are often collectively labelled social distancing and lockdown. On the 23rd June 2020, Boris Johnson, the Prime Minister of the United Kingdom announced substantial easings of restrictions. This paper examines some of the data he presented. Methods: Generalised additive models, with negative binomial errors and cyclic term representing day-of-week effects, were fitted to data on the daily numbers of new confirmed cases of COVID-19. Exponential rates for the epidemic were estimated for different periods, and then used to calculate R, the reproduction number, for the disease in different periods. Results: After an initial stabilisation, the lockdown reduced R to around 0.81 (95% CI: 0.79, 0.82). This value increased to around 0.94 (95% CI 0.89, 0.996) for the fortnight from the 9th June 2020. Conclusions: Official UK data, presented as the easing of the lockdown was announced, shows that R was already more than half way back to 1 at that point. That suggests there was little scope for the announced changes to be implemented without restarting the spread of the disease.
787 downloads medRxiv health policy
The aim of the present work is to estimate capacities of Brazils health system and their demand as a result of predicted incoming severe cases of the novel coronavirus disease (COVID-19) outbreak. Three incrementing levels of hospital equipment usage are considered: (1) in terms of available intensive care unit (ICU) beds; (2) available ICU beds and existing surgery operating rooms; and (3) available ICU beds and existing surgery operating rooms and respirators located in other hospital areas. The average available (adult) ICU beds in a hospital has been computed deducting from the number of existing beds the equivalent number of beds that has been demanded during 2019 on a monthly average. Based on a reference mean duration of hospitalization for the disease, it is computed the daily admission capacity of infected patients per state and of the entire country for each of the three referred levels of hospital equipment usage. Furthermore, an exponential regression model is fitted using the daily available data for the number of patients who have been documented as infected in Brazil. It can then be predicted the three dates at which the health system might begin to demonstrate stress for the maximum demand of the three incrementing groups of hospital equipments. The necessary public data are analyzed by means of the Python programming language and are made available on the internet by the Department of Health Informatics of Brazil (DATASUS - Departamento de Informatica do Sistema Unico de Saude) and the Brazilian Institute of Geography and Statistics (IBGE - Instituto Brasileiro de Geografia e Estatistica).
786 downloads medRxiv health policy
Vaccine hesitancy has been on the rise throughout much of the world for the past two decades. At the same time, existing pro-vaccination public health communication strategies have proven ineffective. We present a novel approach to increase vaccination intentions, which appeals to individuals' other-regarding preferences. Specifically, we assess how vaccination intentions are influenced by the presence of people who cannot vaccinate, such as the immunosuppressed, newborns or pregnant women, using a game where there is a passive player whose welfare depends on the decisions of other, active players. Results from a survey experiment targeting parents and from a laboratory experiment provide support for a twofold positive effect of the presence of the passive player on vaccination intentions. These findings suggest messages that invoke altruistic, other-regarding preferences may be an effective approach to increasing vaccination intentions. Our findings could be extended to other campaigns where the population is invited to adopt behaviors that can help the most susceptible people, as is the case of the self-quarantine measures adopted during the outbreak of CoVID-19 at the beginning of 2020. If the attention of people is focused on the positive effect that they can have on those that cannot protect themselves, then the message may be more effective and people may be more responsive.
782 downloads medRxiv health policy
1.BackgroundAutism is associated with reduced life expectancy, poor physical and mental health, and increased prevalence of epilepsy, obesity, hypertension, diabetes and stroke. AimTo quantify self-reported barriers to healthcare and their consequences amongst autistic adults and compare with parents of autistic children and non-autistic controls Design and SettingAn online survey was developed from a qualitative study undertaken at Autscape, an autistic conference. MethodThematic analysis of 75 responses was used to develop a 57-item online survey completed by 1,271 autistic adults, 406 parents of autistic children and 303 control subjects. Results: Difficulty visiting a GP was reported by 78.2% of autistic adults, 51.4% of parents and 34.9% of controls. The highest-rated barriers by autistic adults were deciding if symptoms warrant a GP visit (71.9%), difficulty using the telephone to book appointments (60.7%), not feeling understood (55.5%) and difficulty communicating with their doctor (53.0%). A higher rate of adverse health outcomes was reported by autistic adults; untreated physical and mental health conditions, not attending specialist referral or screening programmes, requiring more extensive treatment or surgery due to late presentations, and untreated potentially life threatening conditions. Autistic adults reported a need for online or text based appointment booking, facility to email in advance the reason for consultation, first or last clinic appointment and a quiet place to wait. ConclusionReduction of healthcare inequalities for autistic people requires that healthcare providers understand autistic culture and communication needs. Adjustments for autistic communication needs are as necessary as ramps are for wheelchair users. How this fits inAutistic adults avoid seeking health care due to difficulty making appointments and not feeling understood, which may explain poor health outcomes and increased mortality. O_LIAutism is a neurodevelopmental condition involving social communication challenges. C_LIO_LIAutistic people have poor general health, reduced life expectancy with a mortality gap of 16 to 30 years, and even increased in-hospital mortality. C_LIO_LIReduced healthcare seeking behaviour results from communication challenges, primarily difficulties using the phone to make appointments, not feeling understood, and anxiety which decreases communication abilities. C_LIO_LIAutistic people require reasonable adjustments and support to access healthcare in order to improve outcomes and reduce healthcare inequality. C_LI
779 downloads medRxiv health policy
Background: Lack of trust hinders care seeking, and limits community support for contact tracing, care seeking, information and communication uptake, multisectoral or multi-stakeholder engagement, and community participation. We aimed at exploring how trust might be breached and what implications this may have in COVID-19 pandemic response by the Bangladesh health systems. Methods: We conducted this qualitative research during the pandemic, through seven online focus group discussions, with purposively selected mixed-gender groups of clinicians and non-clinicians (n=50). Data were analyzed through conventional content analysis method. Results: The common thread throughout the findings was the pervasive mistrust of the people in Bangladeshi health systems in its management of COVID-19 pandemic. In addition to the existing health systems weaknesses, few others became evident throughout the progression of the pandemic, namely, the lack of coordination challenges during the preparatory phase as well as the advanced stages of the pandemic. This; compounded by the health systems and political leadership failures, lead to opportunistic corruption and lack of regulations; leading to low quality, discriminatory, or no service at all. These have trust implications, manifested in health seeking from unqualified providers, non-adherence to health advice, tension between the service seekers and providers, disapproval of the governance mechanism, misuse of already scarce resources, disinterest in community participation, and eventually loss of life and economy. Conclusions: Health sector stewards should learn the lessons from other countries, ensure multisectoral engagement involving the community and political forces, and empower the public health experts to organize and consolidate a concerted health systems effort in gaining trust in the short run, and building a resilient and responsive health system in the long.
767 downloads medRxiv health policy
As COVID-19 spread in 2020, most countries shut down schools in the hopes of slowing the pandemic. Yet, studies have not reached a consensus about the effectiveness of these policies partly because they lack rigorous causal inference. Our study aims to estimate the causal effects of school closures on the number of confirmed cases. To do so, we apply matching methods to municipal-level data in Japan. We do not find that school closures caused a reduction in the spread of the coronavirus. Our results suggest that policies on school closures should be reexamined given the potential negative consequences for children and parents.
766 downloads medRxiv health policy
Daily new cases dataset since January 2020 were used to search for evidences of SARS-CoV-2 community transmission as the main nowadays cause of constant infection rates among countries. Despite traditional forms of transmission of this virus (droplets and aerosols in medical facilities), new evidence suggests aerosols forming patterns in the atmosphere as a main factor of community transmission outside medical spaces. Following these findings, this research focused on comparing some countries and the adopted policy used as preventive framework for virus community transmission. Countries social distancing policy aspect, of one to two meters of physical distance, was statistically analyzed from January to early May 2020, and countries were divided into those implementing only social physical distance and those implementing distancing with additional transmission isolation (with masks and city disinfection). Correlating countries social distancing policy adoption with other preventive measures such as social isolation and COVID-19 testing, a new indicator results, derived from SIR models and Weibull parameterization, show that only social physical distance measure could act as a factor for SARS-CoV-2 transmission with respect to atmosphere carrier potential. In this sense, the type of social distancing framework adopted by some countries without additional measures might represent a main model for the constant reproductive spread patterns of SARS-CoV-2 within the community transmission. Finally, the findings have important implications for the policy making to be adopted globally as well as individual-scale preventive methods.
759 downloads medRxiv health policy
The purpose of this paper is to compare the relative mitigation efficiency of COVID-19 transmission among 23 selected countries, including 19 countries in the G20, two heavily infected countries (Iran and Spain), and two highly populous countries (Pakistan and Nigeria). This paper evaluated the mitigation efficiency for each country at each stage by using data envelopment analysis (DEA) tools and analyzed changes in mitigation efficiency across stages. Pearson correlation tests were conducted between each change to examine the impact of efficiency ranks in the previous stage on subsequent stages. An indicator was developed to judge epidemic stability and was applied to practical cases involving lifting travel restrictions and restarting the economy in some countries. The results showed that Korea and Australia performed with the highest efficiency in preventing the diffusion of COVID-19 for the whole period covering 120 days since the first confirmed case, while the USA ranked at the bottom. China, Japan, Korea and Australia were judged to have recovered from the attack of COVID-19 due to higher epidemic stability.
752 downloads medRxiv health policy
Abstract: There is some consensus in Europe and Asia about high testing rates being crucial to controlling COVID-19 pandemics. There are though misconceptions on what means an effective high testing rate. This paper demonstrates that the rate of tests per detected case (Tests/Case) is the critical variable, correlating negatively with the number of deaths. The higher the Tests/Case rate, the lower the death rate, as this predictor is causally related to contact tracing and isolation of the vectors of the disease. Doubling Tests/Case typically divides by about three the number of deaths. On the other hand, the per capita testing rate is a poor predictor for the performance of policies to fight the pandemics. The number of tests per 1,000 inhabitants (Tests/1,000) tends to correlate positively with the number of deaths. In some cases, high levels of Tests/1,000 just mean an epidemic that ran out of control, with an explosion of cases that demands high testing rates just to confirm the diagnosis of the seriously sick. This study also demonstrates that an early tracing strategy, with a high level of Tests/Case, reduces combined costs of testing and hospitalization dramatically. Therefore, the common claim that tracing strategies are unaffordable by poorer countries is incorrect. On the contrary, it is the most adequate, both from the economic and humanitarian points of view.
739 downloads medRxiv health policy
The COVID-19 outbreak highlights the vulnerability to novel infections, and vaccination remains a foreseeable method to return to normal life. However, infrastructure is inadequate for the whole population to be vaccinated immediately. Therefore, policies have adopted a strategy to vaccinate the elderly and vulnerable population while delaying others. This study uses the Tennessee official statistic from the onset of COVID vaccination (17th of December 2021) to understand how age-specific vaccination strategies reduce daily cases, hospitalization, and death rate. The result shows that vaccination strategy can significantly influence the numbers of patients with COVID-19 in all age groups and lower hospitalization and death rates just in older age groups. The Elderly had a 95% lower death rate from December to March; however, and no change in the death rate in other age groups. The Hospitalization rate was reduced by 80% in this study cohort for people aged 80 or older, while people who were between 50 to 70 had almost the same hospitalization rate. The study indicates that vaccination targeting older age groups is the optimal way to avoid higher transmissions and reduce hospitalization and death rate for older groups.
738 downloads medRxiv health policy
The COVID-19 pandemic has reinforced the need to ensure that strategic and operational approaches to retain high quality, resilient frontline care home workers, who are not registered nurses, are informed by context specific, high quality evidence. We therefore conducted this scoping review to address the question: What is the current evidence for best practice to support the resilience and retention of frontline care workers in care homes for older people? MEDLINE, PubMed, PsycINFO, Embase, MedRxiv, CINAHL, ASSIA, Social Science Premium were searched for literature published between 2010 and 2020. The search strategy employed combinations of search terms to target frontline care workers in care homes for older people and the key concepts relevant to resilience and retention were applied and adapted for each database. Thirty studies were included. Evidence for best practice in supporting the resilience and retention specifically of frontline care workers in care homes is extremely limited, of variable quality and lacks generalisability. At present, it is dominated by cross-sectional studies mostly from out with the UK. The small number of intervention studies are inconclusive. The review found that multiple factors are suggested as being associated with best practice in supporting resilience and retention, but few have been tested robustly. The thematic synthesis of these identified the analytical themes of - Culture of Care; Content of Work; Connectedness with Colleagues; Characteristics and Competencies of Care Home Leaders and Caring during a Crisis. The evidence base must move from its current state of implicitness. Only then can it inform intervention development, implementation strategies and meaningful indicators of success. High quality, adequately powered, co-designed intervention studies, that address the fundamentally human and interpersonal nature of the resilience and retention of frontline care workers in care homes are required.
737 downloads medRxiv health policy
Objective: This study investigates the regional differences in the occurrence of COVID-19 in Brazil and its relationship with climatic and demographic factors by use data from February 26 to April 04, 2020. Methods: A Polynomial Regression Model with cubic adjustments of the number of days of contagion, demographic density, city population and climatic factors was designed and used to explain the spread of COVID-19 in Brazil. Main results: It was evidenced that temperature variation maintains a relationship with the reduction in the number of cases of COVID-19. A variation -3.4% in the number of COVID-19 cases was found for each increase of 1 C. Conclusion: There are evidences that the temperature, has a relative effect in the variation in the number of COVID-19's researched cases. For the reason, it recommends this relationship deserves to be investigated in other tests with more extended time series, wide and with especially non-linear data adjustments.
728 downloads medRxiv health policy
Without vaccines, non-pharmaceutical interventions have been the most widely used approach to controlling the spread of COVID-19 epidemics. Various jurisdictions have implemented public health orders as a means of reducing effective contacts and controlling their local epidemics. Multiple studies have examined the effectiveness of various orders (e.g., use of face masks) for epidemic control. However, orders occur at different timings across jurisdictions and some orders on the same topic are stricter than others. We constructed a county-level longitudinal data set of more than 2,100 public health orders issues by California and its 58 counties pertaining to its 40 million residents. First, we describe methods used to construct the dataset that enables the characterization of the evolution over time of California state- and county-level public health orders dealing with COVID-19 from January 1, 2020 through April 14, 2021. Public health orders are both an interesting and important outcome in their own right and also a key input into analyses looking at how such orders may impact COVID-19 epidemics. To construct the dataset, we developed and executed a search strategy to identify COVID-19 public health orders over this time period for all relevant jurisdictions. We characterized each identified public health order in terms of the timing of when it was announced, went into effect and (potentially) expired. We also adapted an existing schema to describe the topic(s) each public health order dealt with and the level of stricture each imposed, applying it to all identified orders. Finally, as an initial assessment, we examined the patterns of public health orders within and across counties, focusing on the timing of orders, the rate of increase and decrease in stricture, and on variation and convergence of orders within regions.
722 downloads medRxiv health policy
In Africa, while most countries report some COVID-19 cases, the fraction of reported patients is low, with about 20,000 cases compared to the more than 2.3 million cases reported globally as of April 18, 2020. Few African countries have reported case numbers above one thousand, with South Africa reporting 3,034 cases being hit hardest in Sub-Saharan Africa. Several African countries, especially South Africa, have already taken strong non-pharmaceutical interventions that include physical distancing, restricted economic, educational and leisure activities and reduced human mobility options. The required strengths and overall effectiveness of such interventions, however, are debated because of simultaneous but opposing interests in most African countries: strongly limited health care capacities and testing capabilities largely conflict with pressured national economies and socio-economic hardships on the individual level, limiting compliance to intervention targets. Here we investigate implications of interventions on the COVID-19 outbreak dynamics, focusing on South Africa before and after the national lockdown enacted on March 27, 2020. Our analysis shows that initial exponential growth of existing case numbers is consistent with doubling times of about 2.5 days. After lockdown, the growth remains exponential, now with doubling times of 18 days, but still in contrast to subexponential growth reported for Hubei/China after lockdown. Moreover, a scenario analysis of a computational data-driven agent based mobility model for the Nelson Mandela Bay Municipality (with 1.14 million inhabitants) hints that keeping current levels of intervention measures and compliance until the end of April is of insufficient length and still too weak, too unspecific or too inconsistently complied with to not overload local intensive care capacity. Yet, enduring, slightly stronger, more specific interventions combined with sufficient compliance may constitute a viable option for interventions for regions in South Africa and potentially for large parts of the African continent and the Global South.
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!