MHA507 Florida A&M University 9/10 CN9 Leveraging Informatics In Health Sector Report Resource: How to Plot Data onto a Map in Microsoft Excel PDF Read th

MHA507 Florida A&M University 9/10 CN9 Leveraging Informatics In Health Sector Report Resource: How to Plot Data onto a Map in Microsoft Excel PDF

Read the following scenario:

Now that you know where the outbreaks are located and which age groups are most affected, your organization wants to map out the areas that pose the highest exposure risk.

Create a symbols map using Microsoft® Excel® and the data provided in the High Risk Areas document to determine the areas of the country with the most risk.

Review the “Plotting Data onto a Map in Microsoft® Excel® PDF document for instructions on completing this portion of the assignment.

Write a 350- to 525-word report of your analysis of the data.

Include an answer to the following questions:

Which cities (states) are high risk and low risk?
What areas of the country are high risk and low risk?
What else can be deduced after evaluating the chart?

Include your map within the report, not separately. Label as a Figure according to APA formatting. Also, include title and reference pages.

Cite at least 2 scholarly references to support your assignment. Feel free to use supplemental readings as references, if from peer-reviewed journals. DO NOT use “.com” commercial, “.edu” education, “.org” or “.net” proprietary sources. Okay to use one .gov reference, such as CDC or NIH

Format your citations according to APA guidelines. Date
4/24/2017
4/2/2017
4/27/2017
4/27/2017
4/24/2017
4/2/2017
4/7/2017
4/2/2017
4/24/2017
4/23/2017
4/17/2017
4/14/2017
4/9/2017
4/11/2017
4/9/2017
4/29/2017
4/10/2017
4/12/2017
4/2/2017
4/28/2017
4/28/2017
4/3/2017
4/13/2017
4/25/2017
4/24/2017
4/2/2017
4/27/2017
4/27/2017
4/24/2017
4/2/2017
4/7/2017
4/2/2017
4/24/2017
4/23/2017
4/17/2017
4/14/2017
4/9/2017
4/11/2017
4/9/2017
4/29/2017
4/10/2017
4/12/2017
4/2/2017
4/28/2017
4/28/2017
4/3/2017
Cases
189
201
14
272
5
289
95
258
83
109
281
322
76
7
14
98
19
65
30
29
35
61
28
31
23
18
11
146
26
17
12
51
114
187
51
38
215
231
220
5
4
8
3
299
84
9
estimated polulation
8,601,186
4,057,841
2,679,044
2,359,480
1,576,596
1,711,356
1,565,929
1,453,775
1,379,735
1,033,519
1,001,104
920,984
897,536
863,771
890,228
913,939
889,019
766,893
732,144
696,610
662,172
713,549
694,784
647,506
679,318
667,589
661,614
664,304
594,450
620,800
581,949
564,764
537,501
532,703
513,330
501,094
466,203
503,619
501,178
493,799
454,846
485,679
452,061
491,724
426,410
424,256
Bar graph showing t
City
City
New York
Los Angeles
Chicago
Houston
Philadelphia
Phoenix
San Antonio
San Diego
Dallas
San Jose
Austin
Jacksonville
San Francisco
Indianapolis
Columbus
Fort Worth
Charlotte
Seattle
Denver
El Paso
Detroit
Washington D.C.
Boston
Memphis
Nashville
Portland
Oklahoma City
Las Vegas
Baltimore
Louisville
Milwaukee
Albuquerque
Tucson
Fresno
Sacramento
Kansas City
Long Beach
Mesa
Atlanta
Colorado Springs
Virginia Beach
Raleigh
Omaha
Miami
Oakland
Minneapolis
Arlington
New Orleans
Wichita
Tulsa
Minneapolis
Oakland
Miami
Omaha
Raleigh
Virginia Beach
Colorado Springs
Atlanta
Mesa
Long Beach
Kansas City
Sacramento
Fresno
Tucson
Albuquerque
Milwaukee
Louisville
Baltimore
Las Vegas
Oklahoma City
Portland
Nashville
Memphis
Boston
Washington D.C.
Detroit
El Paso
Denver
Seattle
Charlotte
Fort Worth
Columbus
Indianapolis
San Francisco
Jacksonville
Austin
San Jose
Dallas
San Diego
San Antonio
Phoenix
Philadelphia
Houston
Chicago
Los Angeles
New York
New York
Tulsa
Wichita
New Orleans
Arlington
Total
4/13/2017
4/25/2017
4/10/2017
4/12/2017
127
83
248
11
4852
403,045
392,428
396,766
405,486
51125616
0
50
Bar graph showing the cases of virus infection in different cities
50
100
150
200
Number of cases
250
300
350
Running head: REPORT I
Report I
name
September 30, 2019
MHA/507
Professor
REPORT I
2
Data analysis report
Introduction
Data analysis is of the essence when making critical decisions. Through analysis of data
informed decisions that are reliable end up being arrived at (Rutter & Dabney, 2018). Therefore,
in this case, analysis of data on specific cases of people who are infected with a dangerous virus
in different cities, will enable us to make a reliable decision about where to move medical
resources, i.e., to areas that are in urgent need of medical resources due to high number of
infected cases.
Top five cities in terms of infected cases
The top five cities in terms of the number of infected cases are Jacksonville, Miami,
Phoenix, Austin as well as Houston. These five cities had the highest number of infected cases in
comparison to the other forty five cities from which data was collected from. Jacksonville has
322 infected cases, Miami has 299 infected cases, Phoenix has 289 infected cases, Austin has
281 infected cases and lastly, Houston has 272 infected cases. These five cities that have the
highest number of infected cases are in urgent need of medical resources. Therefore, they should
be prioritized when distributing medical resources for dealing with the virus.
Prevalence rate per 100,000 people
The prevalence rate per 100000 people in all the 50 cities is (total number of cases in 50
cities/ total population in the 50 cities)*100000= (4852/51125616)*100000= 9.49. In other
words the number of cases per 100000 people in all the 50 cities was 9.49 cases (Streiner &
Norman, 2009).
What else can be deduced after evaluating the chart?
REPORT I
3
Other than depicting cities that have the highest number of infected cases, the chart also
provides insights on cities that have the lowest number of infected cases. Five cities that have the
lowest number of infected cases include Omaha that has only 3 infected cases, Virginia Beach
that has 4 infected cases, Colorado Springs and Philadelphia that have 5 infected cases, and lastly
Indianapolis that has 7 infected cases.
Bar graph
Bar graph showing the cases of virus infection in different cities
New Orleans
Tulsa
Oakland
Omaha
Virginia Beach
Atlanta
Long Beach
Sacramento
Tucson
Milwaukee
City
Baltimore
Oklahoma City
Nashville
Boston
Detroit
Denver
Charlotte
Columbus
San Francisco
Austin
Dallas
San Antonio
Philadelphia
Chicago
New York
0
50
100
150
200
Number of cases
250
300
350
REPORT I
4
Conclusion
In summary, data analysis depicted that areas which are in urgent need of resources based
on the number of infected cases are Jacksonville, Miami, Phoenix, Austin as well as Houston. On
the other hand, cities that ought to be considered last when distributing medical resources based
on the fact that they have the least number of infected cases are Omaha, Virginia Beach Colorado
Springs, Philadelphia and lastly, Indianapolis.
REPORT I
5
References
Rutter, K., & Dabney, C. (2018). How to Analyze Your Data for Decision-Making | Seer
Interactive. Retrieved 30 September 2019, from
https://www.seerinteractive.com/blog/analyzing-data-for-decisions/
Streiner, D., & Norman, G. (2009). Measures of disease frequency and mortality. Community
Oncology, 6(12), 573-575. doi: 10.1016/s1548-5315(11)70314-x
City
New York
Los Angeles
Chicago
Houston
Philadelphia
Phoenix
San Antonio
San Diego
Dallas
San Jose
Austin
Jacksonville
San Francisco
Indianapolis
Columbus
Fort Worth
Charlotte
Seattle
Denver
El Paso
Detroit
Washington D.C.
Boston
Memphis
Nashville
Portland
Oklahoma City
Las Vegas
Baltimore
Louisville
Milwaukee
Albuquerque
Tucson
Fresno
Sacramento
Kansas City
Long Beach
Mesa
Atlanta
Colorado Springs
Virginia Beach
Raleigh
Omaha
Miami
Oakland
Minneapolis
Date
4/24/2017
4/2/2017
4/27/2017
4/27/2017
4/24/2017
4/2/2017
4/7/2017
4/2/2017
4/24/2017
4/23/2017
4/17/2017
4/14/2017
4/9/2017
4/11/2017
4/9/2017
4/29/2017
4/10/2017
4/12/2017
4/2/2017
4/28/2017
4/28/2017
4/3/2017
4/13/2017
4/25/2017
4/24/2017
4/2/2017
4/27/2017
4/27/2017
4/24/2017
4/2/2017
4/7/2017
4/2/2017
4/24/2017
4/23/2017
4/17/2017
4/14/2017
4/9/2017
4/11/2017
4/9/2017
4/29/2017
4/10/2017
4/12/2017
4/2/2017
4/28/2017
4/28/2017
4/3/2017
Cases
189
201
14
272
5
289
95
258
83
109
281
322
76
7
14
98
19
65
30
29
35
61
28
31
23
18
11
146
26
17
12
51
114
187
51
38
215
231
220
5
4
8
3
299
84
9

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