2d:null 2e:["$","title",null,{"children":"Belgium Vaccination Tracker - Progress of the vaccination campaign | Corona Commissariaat - Taskforce Vaccination | Observable"}] 33:T61f,{ const hover = vl.selectPoint('hover') .encodings('x') .value({DATE: Date.parse(cumulativeDeliveries.slice(-1)[0].DATE)}) .on('mouseover') .toggle(false) .nearest(true); const isHovered = hover.empty(false); const line = vl.markLine() .encode( vl.x().fieldT("DATE").title(null), vl.y().sum("DOSES").title("Number of doses"), vl.color().fieldN("TYPE").title(null).legend({orient: "bottom"}).scale({scheme: "dark2", domain: ["AstraZeneca", "Moderna", "Pfizer/BioNTech", "Janssen (J&J)"]}) ); const base = line.transform(vl.filter(isHovered)); const circle = line.markCircle({size: 50}) .params(hover) .encode(vl.opacity().if(isHovered, vl.value(1)).value(0)); const rule = vl.markRule({stroke: '#aaa', strokeWidth: 1}) .transform(vl.filter(isHovered)) .encode(vl.x().fieldT('DATE')); const date = vl.markText({align: "left", dy: -8, dx: 5, color: "#666"}) .transform(vl.filter(isHovered), vl.aggregate(vl.max("DATE").as("LDATE"))) .encode(vl.x().fieldT('LDATE'), vl.y().value(0), vl.text().fieldT('LDATE')); const label = base.markText({align: 'left', dx: 5, dy: 7}) .encode(vl.text().sum('DOSES').format(",")); const labelBG = base.markText({align: 'left', dx: 5, dy: 7, stroke: 'white', strokeWidth: 2}) .encode(vl.text().sum('DOSES').format(",")); return vl.data(cumulativeDeliveries) .layer(line, rule, circle, labelBG, label, date) .title("Cumulative deliveries") .padding({right: 60}) .width(500) .render(); }34:T477,Immunocompromised may be insufficiently protected after their basic 1-2 dose(s) vaccination. Therefore, in September 2021, they have already received an additional vaccine, which is part of their basic vaccination. They are now eligible to a booster dose with a mRNA vaccine (Pfizer or Moderna). It is recommended to administrate this booster no earlier than 3 months after the last injection of the basic vaccination schedule. The group of immunocompromised people (12+) continuously evolves with the recording of patients by their sickness fund or general practitioner. In total, there are ~325k immunocompromised people (whose ~94% fulfilled their basic vaccination scheme) candidates to receive a booster dose since 24 January 2022. Not all of them are directly eligible due to the recommended time interval since the last injection. The following graph shows **the percentage of immunocompromised people aged 12 years and over who have received booster dose among eligible ones.** Until last update, ${d3.format(".1%")(booster.filter(d => d.REGION === "Belgium")[0].RATIO)} of invited immunocompromised people received a booster dose.35:T450,{ const vaccinated = vl.markBar({opacity: 1}) .encode( vl.x().fieldQ("RATIO").axis({format: "%"})/*.scale({domainMax: 1})*/.title(null), vl.y().fieldN("REGION").title(null).sort(["Flanders"]), vl.color().fieldN("REGION").title(null).sort(["Flanders"]).scale({range: ["#F66D00", "#00b6cb", "#f10096", "#0072f0", "#999999", "#7cb342"]}).legend(null), vl.tooltip([ {field: "REGION", title: "Region"}, {field: "TOTAL", title: "Number of immunocompromised people", format: ","}, {field: "RATIO", title: "Percentage vaccinated with extra dose", format: ".1%"}, ]) ); const text = vl.markText({align: "left", dx: 5}) .encode( vl.x().value("width"), vl.y().fieldN("REGION").title(null).sort(["Flanders"]), vl.color().fieldN("REGION").title(null).sort(["Flanders"]).scale({range: ["#F66D00", "#00b6cb", "#f10096", "#0072f0", "#999999", "#7cb342"]}).legend(null), vl.text().field("LABEL") ); return vl.layer(vaccinated, text) .title("Immunocompromised people with a booster dose") .data(booster) .render(); }36:T50d,""/*md` The following two graphs show the number of **delivered doses versus the number of administered doses**, for Belgium and per federated entity. The first graph shows the **evolution in the time of delivered and administered doses**. There are two lines for "delivered doses": the solid line represents the number of delivered doses to vaccine centres. The number of doses, however, that vaccine centres can extract per unit (vial) can vary between 6 to 7 doses per vial for Pfizer, 10 to 12 for AstraZeneca and Moderna and 5 to 6 for J&J. The dotted line reflects the maximum number of doses. The maximum cannot be reached at all times; it depends on vaccine centre practices and available equipment (for example, zero- to low-dead syringes). This variation is recorded as of the end of March. The second graph shows the **turnaround time**: the average time needed to administer all the doses of a batch delivery. More information about how these values are calculated can be found in the [FAQ](#faq). Now, it takes around ${leadTime[0].DELAY} days to administer the doses that have been delivered to Belgium. *These graphs are interactive. The toggle buttons can be used to filter by region or manufacturer and hovering over the graphs reveals a tooltip with more information.*`*/37:T472,""/*{ const width = "800px"; let result = `

¹ This is the number of administered and registered doses in VaccinNet. Not every administered dose is registered immediately. On average, 50% is registered in vaccinNet on the day of administration. After 4-5 days this is 90%.

`; result += `

² This is the average time between delivery and administration of a vaccine. A minimum of 5 days is needed to distribute the vaccines to the administration points.

`; if (filterRegion === "Brussels") result += `

³ VaccinNet data is based on the domicile of the vaccinated person. Brussels has vaccinated a significant number of people living outside Brussels. An estimate for that number of people is shown in the graph. Note that this additional volume is not subtracted from the total in VaccinNet for other regions.

`; return html`${result}`; }*/38:T47d,""/*{ const width = "800px"; let result = `

`; result += `

² The average time between delivery and aministration of a vaccine. A minimum of 5 days is needed to distribute the vaccines to the administration points. Reservations of second doses in stock also significantly increase the average delay.

`; if (filterType === "Moderna") result += `

³ The delivery of Moderna vaccines is still unpredictable. Therefore, a second dose is reserved for every first dose given. Since these doses are kept in stock till needed, they significantly increase the average lead time for Moderna vaccines.

`; return html`${result}`; }*/39:T4f4,""/*{ const l1 = vl.markLine({color: "#9c755f"}) .encode( vl.x().fieldT("DATE").title(null), vl.y().fieldQ("RATIO").axis({format: "%"}).scale({domain: [0, 1]}).title(null) ); const l2 = vl.markLine({color: "#9c755f", strokeDash: [2, 2]}) .encode( vl.x().fieldT("DATE").title(null), vl.y().fieldQ("RATIO_MAX").axis({format: "%"}).scale({domain: [0, 1]}).title(null) ); const a = vl.markArea({color: "#9c755f", opacity: 0.3}) .encode( vl.x().fieldT("DATE").title(null), vl.y().fieldQ("RATIO").axis({format: "%"}).scale({domain: [0, 1]}).title(null), vl.y2().fieldQ("RATIO_MAX"), vl.tooltip([ {field: "DATE", type: "temporal", title: "Date"}, {field: "DELIVERED", format: ",", title: "Doses delivered"}, {field: "DELIVERED_MAX", format: ",", title: "Max doses delivered"}, {field: "ADMINISTERED", format: ",", title: "Doses administered"}, {field: "RATIO", format: ".1%", title: "% administered"}, {field: "RATIO_MAX", format: ".1%", title: "Min % administered"} ]) ); return vl.layer(a, l1, l2) .data(administeredRatio) .title("Percentage of the delivered doses that are already administered") .width(500) .render(); }*/3a:T5b8,""/*md`### Why are there ${d3.format(",")(Math.max(0, totalDelivered - totalAdministered))} – ${d3.format(",")(totalDeliveredMax - totalAdministered)} doses in stock? * **Delayed registration**: Some doses have been administered but have not yet been captured in the system - this is referred to as a delay in registration. On average, it takes 4-5 days for 90% of the doses to be captured in the system. * **Strategic stock**: ${d3.format(",")(totalStock)} doses. There is small strategic stock per vaccine type at the central hub of the distributor in case of unexpected events. * **Supply-chain turnaround time**: ${d3.format(",")(deliveredLastDays)} – ${d3.format(",")(deliveredLastDaysMax)} doses. It takes 5 days for a vaccine that is available in Belgium to reach an admin point (e.g., vaccination center). This is driven by the time required to check the delivery, organize the deliveries per vaccination centers and transport the vaccines to the admin point. * **Reservation of Moderna doses**: ${d3.format(",")(modernaStock)} doses. We are holding back the second doses for Moderna. This is due to the schedule of deliveries. * **Other**: Other reasons can be the buffer stock built by federated entities in case of emergency, time to send out invitations if delivery scheme was confirmed less than 1 week before the delivery or strategic planning choices from the federated entities (buffer stock at federated entity level,...) `*/3b:T1715,leadTimeGraphByRegion = (filter) => { const width = 700; const x = vl.x().fieldT("DATE").title(null); const y = vl.y().sum("DOSES").title("Number of doses"); const dataVac = cumulativeVaccinations.filter(d => filter === "Belgium" || d.REGION === filter); const dataDeliveries = cumulativeDeliveries.filter(d => filter === "Belgium" || d.REGION === filter); const mappedValues = d3.rollup(dataVac, v => d3.sum(v, d => d.DOSES), d => d.DATE); const dataDelay = leadTimeByRegion(filter).map(d => { d.D_DATE = d3.timeFormat("%Y-%m-%d")(d3.timeDay.offset(new Date(d.DATE), -1 * d.DELAY)); d.M_DATE = d3.timeFormat("%Y-%m-%d")(d3.timeDay.offset(new Date(d.DATE), -1 * d.DELAY/2)); d.DOSES = mappedValues.get(d.DATE); return d; }); if (filter === "Brussels") { const dataDelayAlt = leadTimeByRegion(filter, true); dataDelay.forEach((d, i) => d.DELAY_ALT = dataDelayAlt[i].DELAY); } const hover = vl.selectPoint("hover") .encodings('x') .on('mouseover') .clear('mouseout') .toggle('false') .nearest(true); const vac = vl.markArea({opacity: 0.9}) .data(dataVac) .encode(x, y, vl.color().fieldN("TYPE").scale({range: ["#edc948", "#59a14f", "#76b7b2"]}).title("Administered doses¹")); const vactt = vl.markArea({opacity: 0}) .data(dataVac) .encode(x, y, vl.tooltip([{field: "DATE", type: "temporal", title: "Date"}, {field: "DOSES", aggregate: "sum", format: ",", title: "Administered doses"}])); const vac2 = vl.markArea({opacity: 0.6}) .data(extraDosesBrussels) .encode(x, vl.y().sum("EXTRA"), vl.y2().sum("DOSES"), vl.color().datum("Estimate of additional doses³").scale({range: ["#bab0ac"]})); const del = vl.markLine({interpolate: "step"}) .data(dataDeliveries) .encode(x, y,vl.color().datum(filter === "Belgium" ? "Delivered doses" : "Available doses").scale({range: ["#b07aa1"]})); const delMax = vl.markLine({interpolate: "step"}) .data(dataDeliveries) .encode(x, vl.y().sum("MAX_DOSES").title("Number of doses"), vl.strokeDash().datum(filter === "Belgium" ? "Max delivered doses" : "Max available doses").scale({range: [[2, 2]]}), vl.color().datum(filter === "Belgium" ? "Max delivered doses" : "Max available doses").scale({range: ["#b07aa1"]})); const deltt = vl.markArea({opacity: 0.2, interpolate: "step", color: "#b07aa1"}) .data(dataDeliveries) .encode(x, y, vl.y2().sum("MAX_DOSES").title("Number of doses"), vl.tooltip([{field: "DATE", type: "temporal", title: "Date"}, {field: "DOSES", aggregate: "sum", format: ",", title: filter === "Belgium" ? "Delivered doses" : "Available doses"}, {field: "MAX_DOSES", aggregate: "sum", format: ",", title: filter === "Belgium" ? "Max delivered doses" : "Max available doses"}]) ); const delayRule = vl.markRule({x2Offset: 4, color: "gray", strokeWidth: 1.5}) .data(dataDelay) .transform(vl.filter(hover.empty(false))) .encode(vl.x().fieldT("DATE"), vl.x2().fieldT("D_DATE"), vl.y().fieldQ("DOSES")); const delayLabelBG = vl.markText({stroke: "white", strokeWidth: 2, dy: -5}) .data(dataDelay) .transform(vl.filter(hover.empty(false))) .encode(vl.x().fieldT("M_DATE"), vl.y().fieldQ("DOSES"), vl.text().value({expr: "datum.DELAY + ' days'"})); const delayLabel = delayLabelBG.markText({color: "gray", dy: -5}); const delayLine = vl.markLine({color: "#e15759"}) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY").title("Turnaround time²").scale({domainMin: 0, clamp: true}), vl.strokeDash().datum("Turnaround time").scale({range: [[2,0]]}).legend(filter === "Brussels" ? {orient: "bottom"} : null)); const delayLine2 = vl.markLine({color: "#e15759"}) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY_ALT"), vl.strokeDash().datum("Turnaround time adjusted for additional doses³").scale({range: [[4,2]]}).legend({orient: "bottom", labelLimit: 300})); const delayZone = vl.markArea({opacity: 0.4}) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY"), vl.y2().fieldQ("DELAY_ALT"), vl.color().datum("Turnaround time adjusted for additional doses³").scale({range: ["#e15759"]}).legend(null/*{orient: "bottom", labelLimit: 300}*/)); const delayDateRule = vl.markRule({color: "gray", strokeWidth: 1.5}) .params(hover) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY"), vl.opacity().if(hover.empty(false), vl.value(1)).value(0)); const delayDateDate = vl.markText({color: "gray", align: "left", y: "height", dy: -5, dx: 3}) .data(dataDelay) .transform(vl.filter(hover.empty(false))) .encode(x, vl.text().fieldT("DATE")); const weekLabelFormat = {fill: "gray", align: "left", dx: 5, baseline: "bottom"}; const weeky = vl.y().fieldQ("VALUE"); const weekMarks = []; const numMarks = Math.floor(d3.max(dataDelay, d => d.DELAY)/7); for (let i = 1; i <= numMarks; i++) { weekMarks.push(vl.markRule({stroke: "gray"}).data([{VALUE: 7 * i}]).encode(weeky)); weekMarks.push(vl.markText(weekLabelFormat).data([{VALUE: 7 * i}]) .encode(weeky, vl.x().value(0), vl.text().value(`${i} week${i > 1 ? "s" : ""}`))); } let base = vl.layer(vac, vactt); if (filter === "Brussels") { base = vl.layer(vac, vactt, vac2).resolve({scale: {color: 'independent'}}); } let delayBase = delayLine; if (filter === "Brussels") { delayBase = vl.layer(delayZone, delayLine, delayLine2).resolve({scale: {strokeDash: 'independent'}}); } return vl.vconcat( vl.layer(base, del, delMax, deltt, delayRule, delayLabelBG, delayLabel) .width(width) .resolve({scale: {color: 'independent', strokeDash: 'independent'}}) .title({text: `Turnaround time for ${filter}`, align: "center"}), vl.layer(...weekMarks, delayBase, delayDateRule, delayDateDate).width(width).height(120) ) .resolve({scale: {x: 'shared'}}) .render(); }3c:T16f5,leadTimeGraphByType = (filter) => { const width = 700; const x = vl.x().fieldT("DATE").title(null); const y = vl.y().sum("DOSES").title("Number of doses"); const dataVac = administrations.filter(d => filter === "All" || d.TYPE === filter); const dataDeliveries = cumulativeDeliveries.filter(d => filter === "All" || d.TYPE === filter); const mappedValues = d3.rollup(dataVac, v => d3.sum(v, d => d.DOSES), d => d.DATE); const dataDelay = leadTimeByType(filter).map(d => { d.D_DATE = d3.timeFormat("%Y-%m-%d")(d3.timeDay.offset(new Date(d.DATE), -1 * d.DELAY)); d.M_DATE = d3.timeFormat("%Y-%m-%d")(d3.timeDay.offset(new Date(d.DATE), -1 * d.DELAY/2)); d.DOSES = mappedValues.get(d.DATE); return d; }); if (filter === "Moderna") { const dataDelayAlt = leadTimeByType(filter, true); dataDelay.forEach((d, i) => d.DELAY_ALT = dataDelayAlt[i].DELAY); } const hover = vl.selectPoint("hover") .encodings('x') .on('mouseover') .clear('mouseout') .toggle('false') .nearest(true); const vac = vl.markArea({opacity: 0.9}) .data(dataVac) .encode(x, y, vl.color().fieldN("TYPE").scale({scheme: "dark2", domain: ["AstraZeneca", "Moderna", "Pfizer/BioNTech", "Janssen (J&J)"]}).title("Administered doses¹")); const vactt = vl.markArea({opacity: 0}) .data(dataVac) .encode(x, y, vl.tooltip([{field: "DATE", type: "temporal", title: "Date"}, {field: "DOSES", aggregate: "sum", format: ",", title: "Administered doses"}])); const vac2 = vl.markArea({opacity: 0.6}) .data(dataVac) .transform(vl.calculate("datum.DOSES + datum.DOSE_DIFF").as("STOCK")) .encode(x, vl.y().sum("STOCK"), vl.y2().sum("DOSES"), vl.color().datum("Reserved for second dose³").scale({range: ["#bab0ac"]})); const del = vl.markLine({interpolate: "step"}) .data(dataDeliveries) .encode(x, y, vl.color().datum("Delivered doses").scale({range: ["#b07aa1"]})); const delMax = vl.markLine({interpolate: "step"}) .data(dataDeliveries) .encode(x, vl.y().sum("MAX_DOSES").title("Number of doses"), vl.strokeDash().datum("Max delivered doses").scale({range: [[2, 2]]}), vl.color().datum("Max delivered doses").scale({range: ["#b07aa1"]})); const deltt = vl.markArea({opacity: 0.2, interpolate: "step", color: "#b07aa1"}) .data(dataDeliveries) .encode(x, y, vl.y2().sum("MAX_DOSES").title("Number of doses"), vl.tooltip([{field: "DATE", type: "temporal", title: "Date"}, {field: "DOSES", aggregate: "sum", format: ",", title: "Delivered doses" }, {field: "MAX_DOSES", aggregate: "sum", format: ",", title: "Max delivered doses"}]) ); const delayRule = vl.markRule({x2Offset: 4, color: "gray", strokeWidth: 1.5}) .data(dataDelay) .transform(vl.filter(hover.empty(false))) .encode(vl.x().fieldT("DATE"), vl.x2().fieldT("D_DATE"), vl.y().fieldQ("DOSES")); const delayLabelBG = vl.markText({stroke: "white", strokeWidth: 2, dy: -5}) .data(dataDelay) .transform(vl.filter(hover.empty(false))) .encode(vl.x().fieldT("M_DATE"), vl.y().fieldQ("DOSES"), vl.text().value({expr: "datum.DELAY + ' days'"})); const delayLabel = delayLabelBG.markText({color: "gray", dy: -5}); const delayLine = vl.markLine({color: "#e15759"}) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY").title("Turnaround time²").scale({domainMin: 0, clamp: true}), vl.strokeDash().datum("Turnaround time").scale({range: [[2,0]]}).legend(filter === "Moderna" ? {orient: "bottom"} : null)); const delayLine2 = vl.markLine({color: "#e15759"}) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY_ALT"), vl.strokeDash().datum("Turnaround time adjusted for reservations of second doses³").scale({range: [[4,2]]}).legend({orient: "bottom", labelLimit: 250})); const delayZone = vl.markArea({opacity: 0.4}) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY"), vl.y2().fieldQ("DELAY_ALT"), vl.color().datum("Turnaround time adjusted for reservations of second doses³").scale({range: ["#e15759"]}).legend(null/*{orient: "bottom", labelLimit: 250}*/)); const delayDateRule = vl.markRule({color: "gray", strokeWidth: 1.5}) .params(hover) .data(dataDelay) .encode(x, vl.y().fieldQ("DELAY"), vl.opacity().if(hover.empty(false), vl.value(1)).value(0)); const delayDateDate = vl.markText({color: "gray", align: "left", y: "height", dy: -5, dx: 3}) .data(dataDelay) .transform(vl.filter(hover.empty(false))) .encode(x, vl.text().fieldT("DATE")); const weekLabelFormat = {fill: "gray", align: "left", dx: 5, baseline: "bottom"}; const weeky = vl.y().fieldQ("VALUE"); const weekMarks = []; const numMarks = Math.floor(d3.max(dataDelay, d => d.DELAY)/7); for (let i = 1; i <= numMarks; i++) { weekMarks.push(vl.markRule({stroke: "gray"}).data([{VALUE: 7 * i}]).encode(weeky)); weekMarks.push(vl.markText(weekLabelFormat).data([{VALUE: 7 * i}]) .encode(weeky, vl.x().value(0), vl.text().value(`${i} week${i > 1 ? "s" : ""}`))); } let base = vl.layer(vac, vactt); if (filter === "Moderna") { base = vl.layer(vac, vactt, vac2).resolve({scale: {color: 'independent'}}); } let delayBase = delayLine; if (filter === "Moderna") { delayBase = vl.layer(delayZone, delayLine, delayLine2).resolve({scale: {strokeDash: 'independent'}}); } return vl.vconcat( vl.layer(base, del, delMax, deltt, delayRule, delayLabelBG, delayLabel) .width(width) .resolve({scale: {color: 'independent', strokeDash: 'independent'}}) .title({text: `Turnaround time for ${filter === "All" ? "all vaccines" : filter}`, align: "center"}), vl.layer(...weekMarks, delayBase, delayDateRule, delayDateDate).width(width).height(120) ) .resolve({scale: {x: 'shared', color: 'independent', strokeDash: 'independent'}}) .render(); }3d:T504,cumulativeVaccinations = { const result = []; const regions = Array.from(new Set(vaccinations.map(d => d.REGION))); const ageGroups = Array.from(new Set(vaccinations.map(d => d.AGEGROUP))).sort(); const grouped = d3.group(vaccinations, d => d.REGION, d => d.AGEGROUP, d => d.DATE); regions.forEach(region => { const by_region = grouped.get(region); ageGroups.forEach(agegroup => { const by_age = by_region.get(agegroup); let total1 = 0; let total2 = 0; let total3 = 0; for (let i = 0; i < dates.length; i++) { total1 += by_age?.has(dates[i]) ? d3.sum(by_age.get(dates[i]).filter(d => d.DOSE === "A"), d => d.COUNT) : 0; total2 += by_age?.has(dates[i]) ? d3.sum(by_age.get(dates[i]).filter(d => d.DOSE === "B"), d => d.COUNT) : 0; total3 += by_age?.has(dates[i]) ? d3.sum(by_age.get(dates[i]).filter(d => d.DOSE === "C"), d => d.COUNT) : 0; result.push({DATE: dates[i], REGION: region, AGEGROUP: agegroup, TYPE: "First dose", DOSES: total1}); result.push({DATE: dates[i], REGION: region, AGEGROUP: agegroup, TYPE: "Second dose", DOSES: total2}); result.push({DATE: dates[i], REGION: region, AGEGROUP: agegroup, TYPE: "Single dose", DOSES: total3}); } }); }); return result; }3e:T4e4,leadTimeByRegion = function (filter = "Belgium", alt = false) { const isBelgium = filter === "Belgium"; const result = []; const delivered = Array.from(d3.rollup(cumulativeDeliveries.filter(d => isBelgium || d.REGION === filter), v => d3.sum(v, d => d.DOSES), d => d.DATE).entries()).map(([DATE, DOSES]) => ({DATE, DOSES})); let used = Array.from(d3.rollup(cumulativeVaccinations.filter(d => isBelgium || d.REGION === filter), v => d3.sum(v, d => d.DOSES), d => d.DATE).entries()) .map(([DATE, DOSES]) => ({DATE, DOSES})); if (alt) { used = extraDosesBrussels.map(d => ({DATE: d.DATE, DOSES: d.EXTRA})); } let i = delivered.length - 1; Array.from(used).reverse().forEach(d => { const date = d.DATE; const total = d.DOSES; for (; i >= 0; i--) { if (delivered[i].DOSES > total) continue; const delay = (new Date(date) - new Date(delivered[i].DATE))/(3600*24*1000); result.push({DATE: date, DELAY: delay}); break; } if (i == -1) { const delay = (new Date(date) - new Date(delivered[0].DATE))/(3600*24*1000); result.push({DATE: date, DELAY: delay}); } }); return result; }3f:T485,leadTimeByType = function (filter = "All", alt = false) { const isAll = filter === "All"; const result = []; const delivered = Array.from(d3.rollup(cumulativeDeliveries.filter(d => isAll || d.TYPE === filter), v => d3.sum(v, d => d.DOSES), d => d.DATE).entries()).map(([DATE, DOSES]) => ({DATE, DOSES})); const used = Array.from(d3.rollup(administrations.filter(d => isAll || d.TYPE === filter), v => d3.sum(v, d => alt ? d.DOSES + d.DOSE_DIFF : d.DOSES), d => d.DATE).entries()) .map(([DATE, DOSES]) => ({DATE, DOSES})); let i = delivered.length - 1; Array.from(used).reverse().forEach(d => { const date = d.DATE; const total = d.DOSES; for (; i >= 0; i--) { if (delivered[i].DOSES > total) continue; const delay = (new Date(date) - new Date(delivered[i].DATE))/(3600*24*1000); result.push({DATE: date, DELAY: delay}); break; } if (i == -1) { const delay = (new Date(date) - new Date(delivered[0].DATE))/(3600*24*1000); result.push({DATE: date, DELAY: delay}); } }); return result; }40:[] 31:{"id":"0eaba193a6e4bea8","slug":"belvax","title":"Belgium Vaccination Tracker - Progress of the vaccination campaign","thumbnail":"d24415075cfc05e25d02bb873a01ac86cae8321c113de6147e5b6e21107c7182","access_level":"public","create_time":"$D2021-04-15T09:17:57.575Z","update_time":"$D2022-02-23T10:30:42.583Z","view_time":null,"first_public_time":"$D2021-04-15T09:18:03.968Z","has_unpublished_edits":null,"fork":true,"stars":11,"starred":false,"owner":{"type":"team","id":"1cb0c584724e1aa0","login":"tf-vaccination","name":"Corona Commissariaat - Taskforce Vaccination ","avatar_url":"https://avatars-next.observableusercontent.com/a7e4e75487576e2bd76b6ebd3e626bc8120677d1078cd07bc559132cad0d242d","tier":"starter_2024"},"version":1583,"publish_version":1583,"role":null,"authored":false,"authors":[{"type":"individual","id":"1bb4daa60239f248","login":"tf-vaccination","name":"Corona Commissariaat - Taskforce Vaccination ","avatar_url":"https://avatars-next.observableusercontent.com/a7e4e75487576e2bd76b6ebd3e626bc8120677d1078cd07bc559132cad0d242d","tier":null}],"members":[{"type":"individual","id":"d42baac23e3ffb5f","login":"bmesuere","name":"Bart Mesuere","avatar_url":"https://avatars-next.observableusercontent.com/eb2388e453b68d683131930d7e0b914d9c3d26dc21802c4e3c852e91ae6e1799","tier":null,"role":"editor"},{"type":"individual","id":"1bb4daa60239f248","login":"tf-vaccination","name":"Corona Commissariaat - Taskforce Vaccination ","avatar_url":"https://avatars-next.observableusercontent.com/a7e4e75487576e2bd76b6ebd3e626bc8120677d1078cd07bc559132cad0d242d","tier":null,"role":"editor"},{"type":"individual","id":"9e0692f3f0b39d29","login":"vincentmelis","name":"Vincent Melis","avatar_url":"https://avatars-next.observableusercontent.com/193b466523c449fbda0ee54c1c3475d609cb1aa4f2ecad5cbaf7065a781a99be","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":14,"collection":{"id":"e7cc41ec60819d92","slug":"coronavirus","title":"Coronavirus","owner":{"id":"f35c755083683fe5","login":"observablehq","name":"Observable"}},"type":"notebook","body":{"title":"Belgium Vaccination Tracker - Progress of the vaccination campaign","cells":[{"id":0,"value":"md`# Belgium Vaccination Tracker - Progress of the vaccination campaign \n*This notebook includes deliveries until ${deliveriesLastUpdated}.*\n\nThis is an initiative from the Taskforce Vaccination as part of the Corona Commissariat. This work has been done in collaboration with [Bart Mesuere](https://research.ugent.be/web/person/bart-mesuere-0?2) (UGent).\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":698,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":701,"value":"md`## Vaccine doses purchased by Belgium for administration within Belgium and for international support\n*Last update date: ${deliveriesLastUpdated}*`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":704,"value":"md`The following graphs give an overview of the number of delivered doses per type of vaccine, taking into account the exact date of delivery to Belgium independently of final destination.\n\nWe received a cumulative total of ${d3.format(\",\")(totalDelivered)} doses for all vaccine types.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":709,"value":"vl.markBar()\n .encode(\n // vega works with sunday-based weeks, so offset by one\n vl.x().fieldO(\"DATE_OFFSET\").timeUnit(\"yearweek\").title(null),\n vl.y().sum(\"DOSES\").title(\"Number of doses\"),\n vl.color().fieldN(\"TYPE\").title(null).scale({scheme: \"dark2\", domain: [\"AstraZeneca\", \"Moderna\", \"Pfizer/BioNTech\", \"Janssen (J&J)\"]}),\n vl.tooltip([{field: \"TYPE\", title: \"Vaccine\"}, {field: \"DOSES\", aggregate: \"sum\", title: \"Doses\", format: \",\"}])\n )\n .data(deliveriesByWeek)\n .width(500)\n .title(\"Deliveries by week\")\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":712,"value":"md`The graph below shows the same information. Size of bubble is proportional to the size of the delivery in that week.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":787,"value":"vl.markCircle()\n .encode(\n // vega works with sunday-based weeks, so offset by one\n vl.x().fieldO(\"DATE_OFFSET\").timeUnit(\"yearweek\").title(null),\n vl.y().fieldN(\"TYPE\").title(null).scale({domain: [\"AstraZeneca\", \"Moderna\", \"Pfizer/BioNTech\", \"Janssen (J&J)\"]}),\n vl.size().sum(\"DOSES\").legend(null),\n vl.color().fieldN(\"TYPE\").title(null).legend(false).scale({scheme: \"dark2\", domain: [\"AstraZeneca\", \"Moderna\", \"Pfizer/BioNTech\", \"Janssen (J&J)\"]}),\n vl.tooltip([{field: \"DOSES\", aggregate: \"sum\", title: \"Doses\", format: \",\"}])\n )\n .data(deliveriesByWeek)\n .width(490)\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1334,"value":"The following graph gives details regarding the deliveries effectively to Belgium ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":715,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":393,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1221,"value":"## Donations\n*Last update date: ${deliveries.filter(d => d.REGION.startsWith(\"Donations\")).reverse()[0].DATE}*\n\nOf the doses delivered to Belgium, we donated **${d3.format(\",\")(donationsCovax)}** doses to the Covax initiative and **${d3.format(\",\")(donationsOther)}** doses via bilateral donations.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1234,"value":"vl.markBar()\n .encode(\n vl.x().fieldO(\"DATE\").timeUnit(\"yearweek\").title(null),\n vl.y().sum(\"DOSES\").title(\"Number of doses\"),\n vl.opacity().fieldN(\"REGION\").title(null).legend({orient: \"bottom\"}).scale({domain: [\"Donations - COVAX\", \"Donations - other\"], range: [1, 0.6]}),\n vl.color().fieldN(\"TYPE\").title(null).scale({scheme: \"dark2\", domain: [\"AstraZeneca\", \"Moderna\", \"Pfizer/BioNTech\", \"Janssen (J&J)\"]}),\n vl.tooltip([{field: \"TYPE\", title: \"Vaccin\"}, {field: \"REGION\", title: \"Type\"}, {field: \"DOSES\", aggregate: \"sum\", title: \"Doses\", format: \",\"}])\n )\n .data(deliveries.filter(d => d.REGION.startsWith(\"Donations\")))\n .width(460)\n .title(\"Doses donated\")\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1339,"value":"Please note that other mechanisms to share doses with other countries are not captured within these graphs","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":412,"value":"changelog = md`---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1305,"value":"md`## Immunocompromised people aged 12 years and over eligible to receive a booster dose with a mRNA vaccine\n*Last update date: ${comorbiditiesLastUpdated}*`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1308,"value":"$34","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1325,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1060,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7,"value":"md`## Appendix\n*These are technical parts that are used by the graphs in this notebook. You can safely ignore them.*`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":563,"value":"/*md`## Daily measured turnaround time for Belgium\n*Last update date: ${administrationsLastUpdated}*`*/\n\"\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":519,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":396,"value":"\"\"//md`### Vaccine turnaround time by region`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":109,"value":"\"\"//viewof filterRegion = Radio([\"Belgium\", \"Flanders\", \"Wallonia\", \"Brussels\", \"Ostbelgien\"], {value: 'Belgium', label: \"Filter by region\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":130,"value":"\"\"//lt = leadTimeGraphByRegion(filterRegion)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":453,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":399,"value":"\"\"//md`### Turnaround time by vaccine type\n//*Last update date: ${administrationsLastUpdated}*`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":266,"value":"\"\"//viewof filterType = Radio([\"All\", \"AstraZeneca\", \"Moderna\", \"Pfizer/BioNTech\", \"Janssen (J&J)\"], {value: 'All', label: \"Filter by type\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":270,"value":"\"\"//ltt = leadTimeGraphByType(filterType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":554,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":899,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":901,"value":"\"\"/*md`### Percentage of delivered doses that are already administered\n*Last update date: ${administrationsLastUpdated}*\n\nThe following graph shows the **percentage of administered doses compared to total delivered doses to Belgium**. The current percentage is ${d3.format(\".1%\")(administeredRatio.slice(-1)[0].RATIO_MAX)} – ${d3.format(\".1%\")(administeredRatio.slice(-1)[0].RATIO)}.\n`*/\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":896,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":521,"value":"\"\"/*faq = md`## FAQ\n*Last update date: ${deliveriesLastUpdated}*`*/","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":527,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":950,"value":"\"\"/*md`### What is the turnaround time?\nThe turnaround time is the average time between the delivery of a vaccine and its administration. It is calculated by taking the cumulative number of administered (and registered) doses on a certain day and counting how many days ago these doses were delivered. You can interpret this as the horizontal gap between de *delivered* and *administered* curves. \n\nThe turnaround time is an average value and can be influenced by several components such as supply-chain turanround time, time to send out invitations and reservations of second doses.`*/\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":540,"value":"\"\"/*md`### Why are there reserved doses for the Moderna vaccine?\nAt the moment, there are ${d3.format(\",\")(modernaStock)} reserved second doses in stock. We are holding back the second doses for Moderna. This is due to the schedule of deliveries. \n\nAs a consequence of this, the average turnaround time for Moderna vaccines is higher.\nTime between first and second dose for Moderna is fixed at 28 days.\n`*/","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":538,"value":"\"\"/*md`### Why is there a gap between delivered and administered for Brussels? What do the additional doses refer to?\nVaccinNet data is based on the domicile of the vaccinated person. Brussels has vaccinated a significant number of people living outside Brussels (this was especially the case when vaccinating healthcare personnel). An estimate for that number of people is shown in the graph as “estimate of additional doses for Brussels”.\n\nNote that this additional volume is not subtracted from the total in VaccinNet for other regions nor shown on Sciensano. Also note that this can further grow going forward and so will be adapted accordingly.\n`*/","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":839,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":845,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":38,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":247,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"vaccinations = (await fetch(\"https://epistat.sciensano.be/Data/COVID19BE_VACC.json\")).json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":22,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":893,"value":"administeredRatio = {\n const result = [];\n const dates = Array.from(new Set(cumulativeDeliveries.map(d => d.DATE)));\n const adminByDate = d3.rollup(administrations, v => d3.sum(v, d => d.DOSES), d => d.DATE);\n const deliverByDate = d3.rollup(cumulativeDeliveries, v => ({D:d3.sum(v, d => d.DOSES), MD:d3.sum(v, d => d.MAX_DOSES)}), d => d.DATE);\n dates.forEach(date => {\n result.push({DATE: date, DELIVERED: deliverByDate.get(date).D, DELIVERED_MAX: deliverByDate.get(date).MD, ADMINISTERED: adminByDate.get(date), RATIO: adminByDate.get(date) / deliverByDate.get(date).D, RATIO_MAX: adminByDate.get(date) / deliverByDate.get(date).MD });\n });\n return result.filter(d => d.RATIO);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1008,"value":"brusselsAlt = (date, doses) => {\n const ratio = 1 + (130000 / d3.sum(cumulativeVaccinations.filter(d => d.REGION === \"Brussels\" && d.DATE === \"2021-06-22\"), d => d.DOSES));\n if (new Date(date) <= new Date(\"2021-06-22\")) {\n return Math.floor(doses * ratio);\n }\n return doses + 130000;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1016,"value":"extraDosesBrussels = {\n const result = [];\n const mapping = d3.rollup(cumulativeVaccinations.filter(d => d.REGION === \"Brussels\"), v => d3.sum(v, d => d.DOSES), d => d.DATE);\n mapping.forEach((doses, date) => {\n result.push({DATE: date, DOSES: doses, EXTRA: brusselsAlt(date, doses)});\n });\n return result;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":100,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":252,"value":"$3f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":61,"value":"leadTime = leadTimeByRegion()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"dates = {\n const result = [];\n let day = d3.timeFormat(\"%Y-%m-%d\")(d3.timeDay.offset(Date.parse(vaccinations[0].DATE), -1))\n const lastDay = vaccinations.slice(-1)[0].DATE\n while (day !== lastDay) {\n day = d3.timeFormat(\"%Y-%m-%d\")(d3.timeDay.offset(Date.parse(day), 1));\n result.push(day);\n }\n return result;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1215,"value":"donationsCovax = d3.sum(deliveries.filter(d => d.REGION === \"Donations - COVAX\"), d => d.DOSES)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1218,"value":"donationsOther = d3.sum(deliveries.filter(d => d.REGION === \"Donations - other\"), d => d.DOSES)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":847,"value":"import {administrations, administrationsLastUpdated} from \"@tf-vaccination/data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1289,"value":"import {cumulativeDeliveries as cDeliveries} from \"@tf-vaccination/data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1295,"value":"cumulativeDeliveries = cDeliveries.filter(d => !d.REGION.startsWith(\"Donations\"))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":856,"value":"import {deliveries, deliveriesByWeek, deliveriesLastUpdated} from \"@tf-vaccination/data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1040,"value":"import {comorbidities, comorbiditiesLastUpdated} from \"@tf-vaccination/data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1298,"value":"import {booster} from \"@tf-vaccination/data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":861,"value":"import {totalDelivered, totalDeliveredMax, totalAdministered, totalStock, totalOther, modernaStock, deliveredLastDays, deliveredLastDaysMax} from \"@tf-vaccination/data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"import {vl} from '@vega/vega-lite-api-v5'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"import {Radio, Table} from \"@observablehq/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W40","stdlib":"1","titling":"auto"}} 32:"$31:body"