Abstract

A strong evidence base is needed to understand the socioeconomic implications of the coronavirus pandemic for the Solomon Islands. High Frequency Phone Surveys (HFPS) are set up to understand these implications over the years. This data is the fifth of the five planned rounds of mobile surveys. Four rounds of the HFPS are already completed in June 2020 (Round 1), Dec 2020-Jan 2021 (Round 2), July-Aug 2021 (Round 3) and Jan 2022-Feb 2022 (Round 4), Round 5 interviewed 2,507 households across the country between July 30, 2022, and September 8, 2022, on topics including vaccines of COVID-19, employment, income, food security, health, and coping strategies, and public trust and security.

Geographic coverage

Urban and rural areas of Solomon Islands.

Analysis unit

Household and Individual.

Universe

All respondents must be aged 18 and over and have a phone.

Kind of data

Sample survey data [ssd]

Sampling procedure

As the objective of the survey was to measure changes as the pandemic progresses, Round Five data collection sought to re-contact all 2,671 households contacted in Round Four. The protocols for re-contact were a maximum of 3 attempts per caller shift, spaced between 1.5 and 2.5 hours apart depending on whether the phone was busy or there was no answer, and 15 attempts in total. A new survey company (Sistemas) was hired for the fifth round, and the old survey company (Tebbutt) did not provide the phone numbers of the old households contacted in previous rounds. Hence, no returning households can be identified in round 5. In Round Five, Honiara was over-represented in the World Bank HFPS (constituting 47.7 percent of the survey sample). All other provinces were deemed under-represented, with the largest differences being for Malaita and Western, which represented 9.5 percent (Census: 21.4 percent), and 12.5 percent of the survey sample (Census: 21.4 percent), respectively. Urban areas constituted 58.3 percent of the survey sample, compared to a quarter (25.6 percent) of the census. The target geographic distribution for the survey was based on the population distribution across provinces from the preliminary 2019 census results. According to the population census, Honiara constituted almost one quarter (18.0 percent) of the total population. Compensating factors for these differences were developed and included in the re-weighting calculations.

Due to the limited sample sizes outside of Honiara, most results are disaggregated into only three geographic regions: Honiara, other urban areas, and rural areas. For more information on sampling, please refer to the presentation slides provided in the External Resources.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire - that can be found in the External Resources of this documentation - was developed both in English and in Solomons Pijin. The survey instrument for the fifth round consisted of the following modules: -Basic information, -Information about COVID-19, -Vaccines of COVID-19, -Health, -Education, -Access food & food security, -Employment and Income, -Coping strategies, -Public trust and security, -and Assets and wellbeing.

Cleaning operations

At the end of data collection, the dataset was cleaned by the World Bank team. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes. Data was edited using Stata.
The data is presented in three data sets: household data set, individual data set, and child data set. The total number of observations in the household data set is 2,507 in the individual data set and is 1,260 in the child data set. The child data set contains the education information for children of all households who answered this section, the individual data set contains the employment and vaccine information for all individuals, and the household data set contains information about health, access food & food security, coping strategies, public trust and security, and assets and well-being.

The 2019 coronavirus (COVID-19) pandemic revealed the urgent need for the acceleration of vaccine development worldwide. Rapid vaccine development poses numerous risks for each category of vaccine technology. By using the Risklick artificial intelligence (AI), we estimated the risks associated with all types of COVID-19 vaccine during the early phase of vaccine development. We then performed a postmortem analysis of the probability and the impact matrix calculations by comparing the 2020 prognosis to the contemporary situation. We used the Risklick AI to evaluate the risks and their incidence associated with vaccine development in the early stage of the COVID-19 pandemic. Our analysis revealed the diversity of risks among vaccine technologies currently used by pharmaceutical companies providing vaccines. This analysis highlighted the current and future potential pitfalls connected to vaccine production during the COVID-19 pandemic. Hence, the Risklick AI appears as an essential tool in vaccine development for the treatment of COVID-19 in order to formally anticipate the risks, and increases the overall performance from the production to the distribution of the vaccines. The Risklick AI could, therefore, be extended to other fields of research and development and represent a novel opportunity in the calculation of production-associated risks.

This feature layer is part of SDGs Today. Please see sdgstoday.orgThe Launch and Scale Speedometer, led by the Duke Global Health Innovation Center, has tracked COVID-19 vaccine purchase agreements between November 2020 and June 2022. This dataset provides the most recent data on vaccine purchases and negotiations by individual countries and unilateral partnerships from 16 companies. Unilateral partnerships include the African Union, European Union, Latin America excluding Brazil, and COVAX, the global initiative aimed to produce, procure, and distribute vaccines to member countries.So far, 14.9 billion doses have been reserved. Confirmed doses are deals that have been signed and finalized. Potential doses include both deals that are under negotiation (not yet final) and also options for additional doses as part of existing confirmed deals.For more information, contact info@launchandscalefaster.org

Abstract: In March 2020, shortly after the World Health Organisation declared COVID-19 a global pandemic, Facebook (the company is now rebranded as Meta) announced steps to stop the spread of COVID-19 and vaccine-related misinformation. This entailed identifying and removing false and misleading content that could contribute to “imminent physical harm”. For other types of misinformation the company’s fact-checking network was mobilised and automated moderation systems ramped up to “reduce its distribution”. In this paper we ask how effective this approach has been in stopping the spread of COVID-19 vaccine misinformation in the Australian social media landscape? To address this question we analyse the performance of 18 Australian right-wing and anti-vaccination Facebook pages, posts and commenting sections collected over 2 years until July 2021. We use CrowdTangle’s engagement metrics and time series analysis to map key policy announcements (between Jan 2020 and July 2021) against page performance. This is combined with content analysis of comments parsed from 2 pages, and a selection of posts that continued to overperform during this timeframe. The results showed that the suppression strategy was partially effective, in that the performance of many previously high performing pages showed steady decline between 2019 and 2021. Nonetheless, some pages not only slipped through the net but overperformed, proving this strategy to be light-touch, selective and inconsistent. The content analysis shows that labelling and fact-checking of content and shadowbanning responses were resisted by the user community who employed a range of avoidance tactics to stay engaged on the platform, while also migrating some conversations to less moderated platforms.

The spread of the COVID-19 Delta variant has prompted many governments, schools, and companies to institute vaccine mandates. Proponents suggest that mandates will enhance public health and increase vaccination rates. Critics suggest that evidence of mandates’ effectiveness is unclear and warn that mandates risk increasing societal inequalities if unvaccinated minority groups opt out of educational, commercial, and social activities where mandates are required. We conduct an original survey experiment on a representative sample of 1,245 Americans to examine the efficacy and effect of COVID-19 mandates. Our findings suggest that mandates are unlikely to change vaccination behavior overall. Further, they may increase the likelihood that sizable percentages of the population opt out of activities where vaccines are mandated. We conclude that mandates that do go into effect should be accompanied by targeted, persuasive communications targeted to specific information needs and identities.

Projet Het LINK-VACC draagt bij aan de post-autorisatiesurveillance van COVID-19 vaccins gegevens uit verschillende bestaande Database anken te koppelen aan gegevens uit het vaccinregister (Vaccinnet +). Vaccinnet + bevat gegevens aantal over de vaccinatie die de Opvolging van enkele belangrijke indicatoren mogelijk maken (aantal toegediende vaccins en vaccinatiegraad per leeftijd, geslacht, type vaccin en plaats). Het koppelen aan andere complementaire Database staat toe om de volgende doelstellingen te bereiken: (1) bepalen van de vaccinatiegraad per specifieke doelgroep (bv. zorgprofessional, personen ouder dan 65 jaar met comorbiditeiteiten); (2) bepalen van de efficaciteit van het vaccin in het voorkomen van laboratorium-bevestigde COVID-19 een tesest-negatief cascontrol studiedesign (par type vaccin, doelgroep, tijd sinds vaccinatie...) en porte het opvolgen van vaccinfalen. (3) Ondersteuning van het Federaal Agentschap voor Geneesmiddelen en Gezondheidsproducten bij missies inzake veiligheid en Kwaliteitscontrole van de vaccins door identificatie en karakterisering van break-through gevallen (gevallen van COVID-19 bij volledig gevaccineerde personen).

Association between subjects’ misinformation, perception and vaccine acceptance (n = 484).

Knowledge of COVID-19 and COVID-19 vaccine among participants (n = 377).

Covid-19 misinformation (n = 484).

Perception of participants towards COVID-19 (n = 377).

Where no reference is provided, values were assumed. Values shown with an asterisk (*) were considered in sensitivity analyses. The transmission rate, β, was calibrated to yield R0 = 2.5 using the next generation matrix method. Transmission rate shown is for primary parameters but was recalibrated for each set of sensitivity analyses.