the gwinnett, newton, and rockdale county health

The Gwinnett, Newton, and Rockdale County Health Departments COVID-19 Morbidity and Mortality Report and Dashboard Data Guide

The Weekly COVID-19 Morbidity and Mortality Report is published once a week on Tuesdays at 10:30

a.m. The Gwinnett, Newton, and Rockdale COVID-19 Dashboard is updated twice weekly, once on

Tuesdays at 10:20 a.m., and on Fridays at 10:20 a.m. Data is reported to the Gwinnett, Newton, and

Rockdale County Health Departments from numerous partners such as commercial labs, hospitals, and

health care providers. All reporting goes through the State Electronic Notifiable Disease Surveillance

System (SendSS).

The data that is displayed on our weekly COVID-19 Morbidity and Mortality Report and on our COVID-19

Dashboard reflect the information that has been reported to Public Health. This information does not

reflect all current tests or cases due to delays in reporting test results to Public Health.

Below you will find information on key terms that can be useful when trying to understand COVID-19

data presented in our reports as well as a description of different data indicators, data limitations, and

frequently asked questions.

Key Terms

1. Case: Someone who has tested positive for COVID-19. The most reliable laboratory test performed

on an individual (as well as other factors) will determine that person’s status as probable or

confirmed case. For example, individuals who have tested positive on an antigen test (see number 4.

COVID-19 Test Types for more details on antigen tests) are considered probable cases. For the

purposes of this data dictionary, every time the word “case” is mentioned it means both confirmed

and probable cases.

2. Close contact: An individual who is not fully vaccinated against COVID-19 and has been within 6 feet

of a COVID-19 case for a total of 15 minutes within a 24-hour period while the case in infectious.

This is regardless of mask usage.

3. COVID-19: Coronavirus disease 2019.

4. COVID-19 Test Types: There are three different groups of tests currently available for COVID-19.

Some tests are used to diagnose and treat clinical infections with COVID-19, and some tests are used

to determine if someone may have been exposed to the virus that causes COVID-19 (SARS-CoV-2).

Find more information on the specific test types below:

a. Molecular (PCR) tests detect the genetic material of the virus and indicate active virus and

infection. PCR tests can be administered by collecting either a nose, nose and throat, or

throat specimens.

b. Antigen Tests detect the presence of proteins called antigens and indicate active virus and

infection. Antigen tests are performed by collecting nose specimens.

c. Serology tests detect the presence of antibodies, which may indicate that someone has

been previously infected or exposed to SARS-CoV-2. Serology tests are administered by

collecting a blood specimen.

5. Date of report: The date a case, outbreak, or contact is reported to the health department. This

does not reflect the date symptoms began or the date the positive specimen was collected. Some

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individuals are reported to the health department days, weeks, or months after their positive test

result due to some reporting delays.

6. Incubation period: The incubation period for COVID-19 is 2 – 14 days. This means that after an

exposure to COVID-19 it can take anywhere from 2 – 14 days for the individual who was exposed to

develop symptoms or if asymptomatic, to test positive.

7. Infectious period: This is the time that a person who is infected with COVID-19 is able to spread the

disease to others. Based on current information the infectious period for individuals is a minimum of

10 days after their symptom onset if they are symptomatic, and 10 days from positive test date if

they are asymptomatic. It is possible that individuals infected with COVID-19 could be infectious for

longer than 10 days (please see isolation guidelines). Individuals are also considered infectious 2

days before their symptom onset, and 2 days before their positive test date if they are

asymptomatic.

8. Outbreak: An outbreak of COVID-19 occurs when a facility experiences a greater than expected level

of illness due to COVID-19 OR in high risk settings, when a facility experiences a single case. The

Georgia Department of Public Health determines the definition of an outbreak for different settings

based on the latest scientific information. Because of this, the definition of a COVID-19 outbreak is

subject to change. Below you can find examples of what is considered an outbreak based on the

setting.

a. Outbreaks in facilities such as long-term care/assisted-living facilities, jails/prisons, or other

congregate residential facilities are defined as one confirmed or suspected case of COVID-19

in these settings.

b. For other settings it is the occurrence of 2 or more COVID-19 cases.

c. Multiple cases in a single household are not considered an outbreak.

9. Percent Positive: Is the percent of positive test results out of all test results reported to Public

Health. Currently percent positive is calculated for combined PCR and Antigen tests.

10. SARS-CoV-2: This is the virus that causes the disease COVID-19. It stands for severe acute respiratory

syndrome coronavirus 2.

11. Fully Vaccinated: An individual is considered fully vaccinated against COVID-19 when they have

received 2 doses of a two dose series, or one dose of a single dose series of an approved COVID-19

vaccine and it has been more than 14 days since their last dose was administered.

Data Descriptions – Morbidity and Mortality Report

District Overview, Gwinnett Overview, Newton Overview, and Rockdale Overview

1. “Confirmed Cases”: This number represents confirmed cases only, defined as individuals with a

positive molecular test result. Only molecular test results are used in identifying confirmed cases.

These test results are reported through multiple sources including electronic lab reporting (ELR),

State Electronic Notifiable Disease Surveillance System (SendSS), faxed case reports, and calls from

providers to the Georgia Department of Public Health. Confirmed cases totals are cumulative.

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2. “Probable COVID-19 Cases”: This number represents probable cases only, defined as individuals with

a positive antigen test result, individuals clinically diagnosed with COVID-19 with epidemiological

linkage to a confirmed case with no confirmatory lab testing, and individuals where a death

certificate lists COVID-19 disease or SARS-CoV-2 as an underlying cause of death or a significant

condition contributing to death. Probable case totals are cumulative.

3. “Total Cases”: Represents the total confirmed and probable COVID-19 cases by county of residence.

4. “Total Deaths”: This number includes COVID-19 cases that were either reported to Public Health as

deceased by healthcare providers, medical examiners/coroners, identified by death certificates with

COVID-19 indicated as the cause of death, or identified during an interview attempt. Totals

presented on the Morbidity and Mortality Report reflect the total confirmed and probable deaths by

county of residence.

a. % of total deaths represents the percentage of deaths among all cases.

b. Some suspected COVID-19 related deaths are under review, therefore, until it is confirmed

that COVID-19 was a contributing factor to death those individuals will not be represented

in our counts.

5. “Hospitalizations”: This number includes confirmed and probable COVID-19 cases that were

hospitalized at the time that case was reported to Public Health, or when the case was interviewed.

This number does not capture hospitalizations that happen after the case has been interviewed. This

number does not represent the number of COVID-19 cases that are currently hospitalized.

6. “Underlying Conditions”: Represents whether a case has had any comorbid or simultaneously

existing diseases or underlying conditions that would make the individual more susceptible to

severe outcomes. The data reflects reports to Public Health during the initial report or during a case

interview. If the status of one of the below comorbidities is unknown, then the individual’s

underlying conditions status is unknown. If an individual has at least one of the comorbidities listed

below then they are classified in the total as having an underlying condition. If individuals do not

have any comorbidities they are listed as “underlying conditions, no”. Underling conditions include:

a. Chronic Lung Disease

b. Diabetes Mellitus

c. Cardiovascular Disease

d. Chronic Renal Disease

e. Chronic Liver Disease

f. Hypertension/High Blood Pressure

g. Immunocompromised Condition

h. Any disability (neurological, neurodevelopmental, intellectual, physical, vision, or hearing

impairment)

i. Obesity (BMI > 40)

j. Currently Pregnant

k. Current Smoker

l. Former Smoker

m. Other Chronic Diseases

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7. “Total Cases & Deaths by Race”: Represents the total number of cases and deaths distributed by

race and ethnicity. Case counts less than 5 are displayed as <5 to protect confidentiality.

Percentages are also displayed.

8. “Total Positivity”: This table includes the number of positive COVID-19 tests (antigen and PCR), the

total COVID-19 tests (antigen and PCR, total tests include tests that are positive, negative, and

indeterminate), and the percent positive (the percentage of positive tests among all tests). Total

tests and Total positive represent cumulative totals and includes both antigen and PCR test results.

9. “Seven Day”: This includes PCR positive test results ONLY. This row displays the number of PCR

positive tests reported to Public Health during a seven-day period. Beside the number of positive

tests is the percent positive. This represents percent of positive PCR tests among all tests reported in

the last seven days. The date range for this figure can be found on the weekly Morbidity and

Mortality Report on Page 1 in the bottom right-hand corner.

10. “Reported COVID-19 Cases in residents in Gwinnett, Newton, and Rockdale Counties”: This figure

represents the total number of confirmed and probable cases by date of symptom onset.

a. For individuals who are missing symptom onset date, date of first positive specimen

collection is used, if both symptom onset date and positive specimen collection date are

missing then date reported to Public Health is used.

i. There are a couple of reasons an individual may be missing a symptom onset date.

One is that the individual never had symptoms. That is, they were totally

asymptomatic during their illness, so they did not have an onset date. The second

reason is because the individual was never interviewed by Public Health; therefore,

their symptom onset date was never obtained.

b. The 7-day moving average represents the total number of cases over the last 7 days divided

by 7.

c. The 14-day window of uncertainty represents the cases over the last 14 days that may not

be accounted for due to illnesses yet to be reported or test results that may still be pending.

11. “Reported Hospitalizations of COVID-19 cases in residents of Gwinnett, Newton, and Rockdale

counties by date of occurrence”: This figure represents the total number of reported

hospitalizations by date of hospitalization.

a. The 7-day moving average represents the total number of hospitalizations over the last 7

days divided by 7.

12. “Reported Deaths among COVID-19 cases in residents in Gwinnett, Newton, and Rockdale

Counties”: This figure represents the total number of reported COVID-19 related deaths by date of

death.

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13. “Number of Outbreaks by Facility Type”: These graphs represent the total number of outbreaks for

each county, grouped by the type of facility. Facility types are:

a. Businesses

b. Daycare

c. Government

d. Healthcare

e. Jail/Prison

f. Long-term care (LTC)/Assisted-living facilities (ASL)

g. Manufacturing

h. Mental Health Rehab

i. Place of worship

j. School

k. Veterinarian

l. Youth Sports

14. “Number of Outbreaks by County Over Time”: This graph represents the number of outbreaks

reported to Public Health that occurred in Gwinnett, Newton, or Rockdale Counties. The x-axis

represents the month the outbreak is reported to local Public Health. The y-axis represents the

number of outbreaks reported.

15. “Race Distribution of Cases in”: Displays the racial distribution of cases in each county. Graphs are

cumulative.

16. “Age Distribution of Cases in”: Displays the age distribution of cases in each county. The Y-axis

represents each age group, and the x-axis displays the percentage of cases. Percentages are also

displayed at the top of each bar. The graphs are cumulative.

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COVID-19 Vaccinations among District Residents

17. “% of county Residents with at least one dose compared with % of county population”: On pages 5,

7, and 9 of the Morbidity and Mortality report the demographic characteristics of vaccine recipients

who reside in Gwinnett, Newton, or Rockdale are compared to the population living in those

counties who also identify in the same demographic categories. Please see figure 1 below for an

example of the comparison between the races of vaccine recipients living in Gwinnett to the race

characteristics of all Gwinnett county residents. The green bar in figure 1 is the percent of all

Gwinnett residents who identify as that racial group. For example, if the total population of

Gwinnett is 100 individuals, and out of those 100 individuals 30 of them identify as Black the percent

displayed for Black race in the green bar would be 30%. As an example for the blue bar if 100

Gwinnett residents received at least one dose of COVID-19 vaccine and 10 of them identify as Black,

then the percent represented by the blue bar for the Black racial group will be 10%. The examples

and calculations are applicable for all graphs on pages 5, 7, and 9.

a. The calculation for the green bar

𝑇ℎ𝑒 # 𝑜𝑓 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙𝑠 𝑤ℎ𝑜 𝑙𝑖𝑣𝑒 𝑖𝑛 𝑡ℎ𝑒 𝑐𝑜𝑢𝑛𝑡𝑦 𝑖𝑛 𝑡ℎ𝑎𝑡 𝑑𝑒𝑚𝑜𝑔𝑟𝑎𝑝ℎ𝑖𝑐 𝑔𝑟𝑜𝑢𝑝

𝑇ℎ𝑒 𝑡𝑜𝑡𝑎𝑙 # 𝑜𝑓 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙𝑠 𝑤ℎ𝑜 𝑙𝑖𝑣𝑒 𝑖𝑛 𝑡ℎ𝑒 𝑐𝑜𝑢𝑛𝑡𝑦

b. The calculation for the blue bar

𝑇ℎ𝑒 # 𝑜𝑓 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙𝑠 𝑤ℎ𝑜 𝑙𝑖𝑣𝑒 𝑖𝑛 𝑡ℎ𝑒 𝑐𝑜𝑢𝑛𝑡𝑦 𝑖𝑛 𝑡ℎ𝑎𝑡 𝑔𝑟𝑜𝑢𝑝 𝑤ℎ𝑜 ℎ𝑎𝑣𝑒 𝑟𝑒𝑐𝑖𝑒𝑣𝑒𝑑 𝑎𝑡 𝑙𝑒𝑎𝑠𝑡 𝑜𝑛𝑒 𝑑𝑜𝑠𝑒

𝑇ℎ𝑒 𝑡𝑜𝑡𝑎𝑙 # 𝑜𝑓 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙𝑠 𝑤ℎ𝑜 ℎ𝑎𝑣𝑒 𝑟𝑒𝑐𝑖𝑒𝑣𝑒𝑑 𝑎𝑡 𝑙𝑒𝑎𝑠𝑡 𝑜𝑛𝑒 𝑑𝑜𝑠𝑒 𝑖𝑛 𝑡ℎ𝑎𝑡 𝑐𝑜𝑢𝑛𝑡𝑦

Figure 1.

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18. “% if Gwinnett residents who have received at least 1 dose out of all residents in that group”: On

pages 6, 8, and 10 of the Morbidity and Mortality Report the demographgic characteristics of

vaccine recipients who reside in Gwinnett, Newotn, or Rockdale counties are compared with all

individuals in that demographic group. The blue bar represents the % of individuals in that group

who have received at least one dose, and the green bar represents the % of individuals in that group

who have no record of receiving a COVID-19 vaccine. All bars on the graphs total 100% of each

demographic group. For example, if there are 100 individuals who reside in Gwinnett and identify as

Black and out of those 100 individuals 25 of them have received at least one dose of vaccine, the

percentage displayed by the blue bar would be 25%. Conversly, the green bar would represent the

opposite, which is that 75% of individuals who identify as Black in Gwinnett have no history of

receiving a COVID-19 vaccine. See figure 2 for an example of what the graphs look like. The

examples and calculations are applicable to all data on pages 6, 8, and 10.

a. Calculation for the blue bar

# 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑦 𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑠 𝑤ℎ𝑜 ℎ𝑎𝑣𝑒 𝑟𝑒𝑐𝑖𝑒𝑣𝑒𝑑 𝑎𝑡 𝑙𝑒𝑎𝑠𝑡 𝑜𝑛𝑒 𝑑𝑜𝑠𝑒 𝑜𝑓 𝑣𝑎𝑐𝑐𝑖𝑛𝑒 𝑖𝑛 𝑡ℎ𝑎𝑡 𝑔𝑟𝑜𝑢𝑝

# 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑦 𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑠 𝑤ℎ𝑜 𝑖𝑑𝑒𝑛𝑡𝑖𝑓𝑦 𝑖𝑛 𝑡ℎ𝑎𝑡 𝑔𝑟𝑜𝑢𝑝 𝑟𝑒𝑔𝑎𝑟𝑑𝑙𝑒𝑠𝑠 𝑜𝑓 𝑣𝑎𝑐𝑐𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑠𝑡𝑎𝑡𝑢𝑠

b. Calculation for the green bar

# 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑦 𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑠 𝑤ℎ𝑜 ℎ𝑎𝑣𝑒 𝑛𝑜 𝑟𝑒𝑐𝑜𝑟𝑑 𝑜𝑓 𝑟𝑒𝑐𝑖𝑒𝑣𝑖𝑛𝑔 𝑎 𝐶𝑂𝑉𝐼𝐷 − 19 𝑣𝑎𝑐𝑐𝑖𝑛𝑒 𝑖𝑛 𝑡ℎ𝑎𝑡 𝑔𝑟𝑜𝑢𝑝

# 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑦 𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑠 𝑤ℎ𝑜 𝑖𝑑𝑒𝑛𝑡𝑖𝑓𝑦 𝑖𝑛 𝑡ℎ𝑎𝑡 𝑔𝑟𝑜𝑢𝑝 𝑟𝑒𝑔𝑎𝑟𝑑𝑙𝑒𝑠𝑠 𝑜𝑓 𝑣𝑎𝑐𝑐𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑠𝑡𝑎𝑡𝑢𝑠

Figure 2.

Data Definitions – COVID-19 Dashboard

19. “Total cases by ZIP map”: Displays the total number of cases per 100,000 residents, and case counts

by ZIP code. This map is updated twice a week on Tuesday and Friday. The underlying population in

the calculation is taken from the 2018 Census 5-year estimates. In order to be as accurate as

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possible an apportionment method is used to determine the amount of individuals in each ZIP code

that live in our district, for ZIP codes that are split by jurisdictional boundaries. To see case rates

only, just hover over the county of interest to see the case rate. To see the case rate and the case

counts click on any ZIP code of interest to see both. You can also see case rates and case counts on

the export from the map.

a. The population that is used to calculate the two-week case counts is derived from the 2018

5-year census estimates. Due to the fact that several ZIP codes in our district cross

jurisdictional boundaries with other districts, we have adopted MySideWalk’s block

apportionment method to determine the estimated underlying population that lives in our

district for those ZIP codes that cross district boundaries. To determine how much of that

ZIP code lies within our district MySideWalk uses a block apportionment method where the

ZIP code is broken up into Census block groups (smallest possible geography). There is a

geographical dot placed into the center each Census block. If that dot is captured within our

district, then 100% of that population in that census block goes towards the underlying

population. If the dot is not captured in our district boundaries, then none of that

population goes to our underlying population.

b. Case counts that are <5 are not displayed on the map, or on the map export. This is to

protect confidentiality of persons with COVID-19 in these ZIP codes.

20. “Cases in the last 14-days by ZIP”: Displays the number of cases per 100,000 residents by ZIP code,

and case counts that were reported to the health department in the prior 14-day period. The 14-day

period is from Sunday – Saturday before the data is pulled. Data is pulled every Monday at 9:00 am.

This map is only updated once a week on Tuesdays. To see case rates only, just hover over the

county of interest to see the case rate. To see the case rate and the case counts click on any ZIP

code of interest to see both. You can also see case rates and case counts on the export from the

map.














21. “Hospitalizations by ZIP”: Displays the total number of hospitalizations among COVID-19 cases

reported to the health department per 100,000 residents by ZIP code, and case counts This map is

updated twice weekly on Tuesdays and Fridays. To see case rates only, just hover over the county of

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interest to see the case rate. To see the case rate and the case counts click on any ZIP code of

interest to see both. You can also see case rates and case counts on the export from the map.














22. “Deaths by ZIP”: Displays the total number of deaths among COVID-19 cases reported to the health

department per 100,000 residents, and case counts by ZIP code. This map is updated twice weekly

on Tuesdays and Fridays. To see case rates only, just hover over the county of interest to see the

case rate. To see the case rate and the case counts click on any ZIP code of interest to see both. You

can also see case rates and case counts on the export from the map.







ZIP code us broken up into Census block groups (smallest possible geography). There is a







Trends

The trends section includes three different graphs. The graphs included in this section of the report

include: New Cases by Date, Cumulative Cases by Date, and Cumulative Deaths by Date.

23. “New Cases by Date”: Displays the number of cases by day of symptom onset. If date of symptom

onset is not available, the date of first positive specimen collection is used. If neither date of

symptom onset nor date of first positive specimen collection are available, the date of report to

Public Health is used. The graph is broken up by county. The 14-day window represents reported

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cases over the last 14-days and may not include all cases who become ill during this time due to

illness yet to be reported or test results that may be pending.

24. “Cumulative Cases by Date”: Displays the cumulative number of cases by day of symptom onset. If

the date of symptom onset is not available, the date of first positive specimen collection is used. If

neither date of symptom onset nor date of first positive specimen collection are available, the date

of report to Public Health is used. The graph is broken up by county. The 14-day window represents

reported cases over the last 14-days and may not include all cases who become ill during this time

due to illness yet to be reported or test results that may be pending.

25. “Cumulative Deaths by Date”: Displays the cumulative number of cases by date of death. The graph

is broken up by county. The 14-day window represents reported deaths over the last 14-days and

may not include all individuals who become deceased during this time due to death yet to be

reported or test results that may still be pending. Some suspected COVID-19 related deaths are

under review, therefore, until it is confirmed that COVID-19 was a contributing factor to death those

individuals will not be represented in our counts.

County Specific Pages

26. “Cases by Age”: Displays the age distribution among cases for each county. Percentages are

displayed on each slice of the pie graph. When you hover over each slice of the pie graph, the case

count is displayed. There are 12 age groups. Individuals with missing age are not displayed in this

graph. The graph is cumulative.

27. “Cases by Sex”: Displays the sex distribution among cases in each county. Percentages are displayed

on each slice of the pie graph. When you hover over each slice of the pie graph, case counts are

displayed. The graph is cumulative.

28. “Cases by Race and Ethnicity”: Displays two pie graphs. One pie for race and another for ethnicity.

Percentages are displayed on each pie slice. If you hover over the slice of the pie graph, case counts

are displayed. The graphs are cumulative.

Data Limitations

Due to this pandemic's evolving nature and the immediate need to collect and report COVID-19 related

data, everything presented in our report is provisional. This means that the data is continuously

changing, and information presented on one day may be different from the next. There is an extreme

amount of effort put into the continuous cleaning, validation, and maintaining of our data for accuracy

and clarity; however, due to the vast amount of data collected each day, the cleaning process is ongoing

and may be delayed. Presented here is a detailed explanation of the limitations of the data.

All the data presented in our reports rely heavily on individual report at the time of the interview. If an

individual develops symptoms or becomes hospitalized due to their COVID-19 illness after their initial

interview, that information is likely missed. This will lead to an underrepresentation of hospitalizations

and illness characteristics in the data. Also, during the interview process, information may be omitted

due to the individual's inability to recall information at the time of the interview or lack of willingness to

divulge information to the case investigator. Therefore, this will lead to bias in the data. Due to a

significant delay in cases being reported to Public Health, numbers presented in all of our reports are

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likely undercounts of our community's actual disease burden. This considerable delay in reporting

affects multiple different variables.

There are also limitations associated with age-related data. There are two ways in which age-related

data is reported to Public Health. It is either: 1. reported to Public Health from a third party such as a

commercial lab, hospital, physician’s office, or testing facility; or, 2. it is reported to Public Health at the

time of the interview with the patient. Age-related data that is reported to Public Health from a third

party can be incomplete. During the case investigation process, Public Health has the opportunity to

confirm that age-related information reported through these third parties is correct. However, due to

the significant number of cases reported to Public Health daily, it is impossible to interview everyone

who has tested positive for COVID-19. Based on this, there may be some age-related data that cannot

be confirmed for accuracy. Even though not all individuals can be interviewed, there are data cleaning

processes to ensure the accuracy and reliability of the data we present, but that cleaning is ongoing.

During an interview case investigators are able to confirm age-related data to ensure accuracy.

However, due to the significant amount of cases reported to Public Health daily, not every case will be

interviewed. Therefore, the opportunity to confirm the date of birth during interview is missed and the

date of birth reported to Public Health through the first two mechanisms cannot be confirmed. Due to

this, there is the potential that age-related data is incorrect or missing. Even though this opportunity to

confirm date of birth is missed, there is effort to confirm age-related data through data cleaning.

There are also some significant limitations associated with hospitalization-related data. As stated earlier,

hospitalizations that occur after the case is reported to Public Health are likely missed. This can lead to

an underestimation of the number of individuals who are hospitalized due to COVID-19. However, there

is also the possibility that hospitalizations may be misclassified. Some individuals may visit the hospital

and be admitted for reasons unrelated to COVID-19. Some examples are if an individual presents to the

hospital to give birth or due to an unrelated injury. While these individuals are admitted to the hospital

for these other conditions, they may also be tested for COVID-19. If these individuals are then positive

for COVID-19, they may unintentionally be reported as a hospitalization. These individuals may be

reported to Public Health as being hospitalized in these instances, but it may not be due to COVID-19.

Also, there is the possibility that a hospital visit may be classified as a hospitalization. As mentioned

earlier, there is an extreme amount of effort to clean the data presented here. Still, there will be

instances in which hospitalization may be misclassified.

There are also limitations to the PCR and antigen positivity data. PCR and antigen positivity represents

the percentage of total PCR and antigen tests that are positive in our district. Because of the increased

availability of testing in our district, some individuals may be tested multiple times. It has been shown

that some individuals with COVID-19 can test positive for a prolonged period of time after their initial

infection. Therefore, individuals who test positive multiple times will be captured in this data. Also, due

to potential reporting delays, and potential underreporting these numbers are provisional and are

subject to change.

All the limitations presented here should be taken into account when using the data presented in the

weekly Morbidity and Mortality Report, as well as when using the dashboard.

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Frequently Asked Questions

Q: What is the difference between a confirmed case and a presumptive case of COVID-19?

A: A confirmed case of COVID-19 is someone who tested positive using a molecular-based test (a test

detecting the actual genetic material of the virus). A presumptive case of COVID-19 is an individual who

either, tested positive with an antigen based test, is clinically diagnosed with COVID-19 and has

epidemiological linkage to a confirmed case, or has COVID-19 listed as a significant contributing factor to

death on a death certificate. All confirmed and presumptive cases require Public Health follow up and

investigation.

Q: Where does date of death come from?

A: The date of death is based on the date of death reported to Public Health or identified on death

certificate.

Q: What is a case rate, and how is it calculated?

A: Case rates are the number of new cases identified during a specified time person per 100,000

population. It uses the following calculation: (the number of new cases identified during a specific time

period, in a specific geographic area) divided by (the population for that specified area) times 100,000.

The date reported to Public Health is used to determine the time period for case rates displayed by GNR.

Q: What does COVID-19 stand for?

A: Coronavirus disease 2019.

Q: What is SARS-CoV-2?

A: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes COVID-19.

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