Copy master to LuiGazem-patch-1

00-ProjectProposal.ipynb

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 "\n",
 "- Lui Gazem: Analysis, Writing – original draft\n",
 "\n",
-"- Candance Eastep: Background research, Writing – original draft, Writing – review & editing\n",
+"- Cadence Eastep: Background research, Writing – original draft, Writing – review & editing\n",
 "\n",
 "- Ahgean Davis: Data curation, Software, Visualization\n",
 "\n",
@@ -66,7 +66,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-"Mobility rates and COVID-19 case counts exhibited a substantial correlation throughout the pandemic. In response to the rapid spread of the virus, public health authorities urged individuals to remain at home whenever possible, recognizing that increased movement and social interaction heightened the risk of transmission. From the onset of this global crisis, policymakers closely monitored the relationship between population mobility and infection rates in an effort to mitigate uncontrolled surges in cases. A study conducted by the Centers for Disease Control and Prevention (CDC) examined anonymized cell phone GPS data to assess patterns of movement across counties in the United States. The researchers observed that reductions in trips outside the home were associated with subsequent declines in reported COVID-19 cases. Specifically, changes in mobility were analyzed in relation to new case counts approximately 11 days later, reflecting the typical incubation period and reporting delays. The study also compared urban and rural areas to determine whether mobility patterns affected transmission differently across settings. This distinction was critical, as urban centers tend to be more densely populated, exhibit distinct transportation behaviors, and may experience differing timelines of viral introduction and spread compared to rural communities.\n",
+    "Mobility rates and COVID-19 case counts exhibited a substantial correlation throughout the pandemic. In response to the rapid spread of the virus, public health authorities urged individuals to remain at home whenever possible, recognizing that increased movement and social interaction heightened the risk of transmission. From the onset of this global crisis, policymakers closely monitored the relationship between population mobility and infection rates in an effort to mitigate uncontrolled surges in cases. A study conducted by the Centers for Disease Control and Prevention (CDC) examined anonymized cell phone GPS data to assess patterns of movement across counties in the United States. The researchers observed that reductions in trips outside the home were associated with subsequent declines in reported COVID-19 cases. Specifically, changes in mobility were analyzed in relation to new case counts approximately 11 days later, reflecting the typical incubation period and reporting delays. The study also compared urban and rural areas to determine whether mobility patterns affected transmission differently across settings. This distinction was critical, as urban centers tend to be more densely populated, exhibit distinct transportation behaviors, and may experience differing timelines of viral introduction and spread compared to rural communities.\n",
     "\n",
     "For our project, we aim to more closely examine variation in COVID-19 case counts across days of the week, with particular attention to identifying when case spikes are most pronounced. Consistent with our hypothesis, we anticipate that reported cases will be higher during weekdays compared to weekends. One possible explanation is that essential workers continued in-person employment throughout much of the pandemic, increasing opportunities for exposure during the workweek. Workplace environments may facilitate transmission due to repeated close interactions with coworkers and contact with shared surfaces (e.g., counters, equipment, communal appliances). These routine occupational exposures could contribute to elevated transmission risk during weekdays, which may subsequently be reflected in higher reported case counts. This hypothesis is supported by prior empirical work conducted by Hannah Hoffman and The COVID Tracking Project, which examined temporal reporting patterns in state-level COVID-19 case data. Their analysis demonstrated a consistent decline in reported case counts over weekends. Importantly, this pattern was attributed not only to behavioral changes but also to structural factors, including reduced testing, reporting delays, and public health regulations that limited activity during weekends in many states at the time.\n",
     "\n",
@@ -90,6 +90,7 @@
     "We hypothesize that daily COVID-19 case counts (daily_cases) will vary systematically across days of the week, with lower reported cases on weekends (is_weekend = 1) and higher reported cases during weekdays. Additionally, we predict that increases in workplace mobility (workplaces) will be positively associated with daily COVID-19 case counts, while increases in residential mobility (residential) will be negatively associated with daily case counts at the county level over time.\n"
    ]
   },
+
   {
    "attachments": {},
    "cell_type": "markdown",
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    "source": [
 "## Team Expectations\n",
 "\n",
-"Our team members are Nicholas Campos, Lui Gazem, Candance Eastep, Ahgean Davis, and Chuck Davies. We have read and agree to follow the COGS108 Team Policies.\n",
+"Our team members are Nicholas Campos, Lui Gazem, Cadence Eastep, Ahgean Davis, and Chuck Davies. We have read and agree to follow the COGS108 Team Policies.\n",
 "\n",
 "- **Clear Communication:** We will communicate primarily through group chat and scheduled meetings. All members are expected to respond within 24 hours unless previously communicated otherwise. Important decisions will be made during meetings to ensure transparency.\n",
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