SciCompMod · mknaranja · Jul 31, 2025 · Jul 1, 2025 · Jul 1, 2025 · Jul 1, 2025
diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
@@ -22,7 +22,8 @@ Please check our [git workflow](https://memilio.readthedocs.io/en/latest/develop
 - [ ] New code adheres to [coding guidelines](https://memilio.readthedocs.io/en/latest/development.html#coding-guidelines)
 - [ ] No large data files have been added (files should in sum not exceed 100 KB, avoid PDFs, Word docs, etc.)
 - [ ] Tests are added for new functionality and a local test run was successful (with and without OpenMP)
-- [ ] Appropriate **documentation** for new functionality has been added (Doxygen in the code and explanations in the online documentation)
+- [ ] Appropriate **documentation within the code** (Doxygen) for new functionality has been added in the code
+- [ ] Appropriate **external documentation** (ReadTheDocs) for new functionality has been added to the online documentation
 - [ ] Proper attention to licenses, especially no new third-party software with conflicting license has been added
 - [ ] (For ABM development) Checked [benchmark results](https://memilio.readthedocs.io/en/latest/development.html#agent-based-model-development) and ran and posted a local test above from before and after development to ensure performance is monitored.
 

diff --git a/README.md b/README.md
@@ -9,17 +9,17 @@ MEmilio implements various models for infectious disease dynamics, from simple c
 
 If you use MEmilio, please cite our work
 
-- Bicker J, Kerkmann D, Korf S, Plötzke L, Schmieding R, Wendler A, Zunker H et al. (2025)  *MEmilio - a High Performance Modular Epidemics Simulation Software*. Available at `https://github.com/SciCompMod/memilio` and `https://elib.dlr.de/213614/`.
+- Bicker J, Kerkmann D, Korf S, Plötzke L, Schmieding R, Wendler A, Zunker H et al. (2025)  *MEmilio - a High Performance Modular Epidemics Simulation Software*. Available at https://github.com/SciCompMod/memilio and https://elib.dlr.de/213614/ .
 
 and, in particular, for
 
-- Ordinary differential equation-based (ODE) and Graph-ODE models: Zunker H, Schmieding R, Kerkmann D, Schengen A, Diexer S, et al. (2024). *Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios*. *PLOS Computational Biology* 20(12): e1012630. `https://doi.org/10.1371/journal.pcbi.1012630`
-- Integro-differential equation-based (IDE) models: Wendler AC, Plötzke L, Tritzschak H, Kühn MJ. (2024). *A nonstandard numerical scheme for a novel SECIR integro differential equation-based model with nonexponentially distributed stay times*. Submitted for publication. `https://arxiv.org/abs/2408.12228`
-- Agent-based models (ABMs): Kerkmann D, Korf S, Nguyen K, Abele D, Schengen A, et al. (2025). *Agent-based modeling for realistic reproduction of human mobility and contact behavior to evaluate test and isolation strategies in epidemic infectious disease spread*. *Computers in Biology and Medicine* 193: 110269. `DOI:10.1016/j.compbiomed.2025.110269 <https://doi.org/10.1016/j.compbiomed.2025.110269>`_
-- Hybrid agent-metapopulation-based models: Bicker J, Schmieding R, Meyer-Hermann M, Kühn MJ. (2025). *Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing*. *Infectious Disease Modelling* 10(2): 571-590. `https://doi.org/10.1016/j.idm.2024.12.015`
-- Graph Neural Networks: Schmidt A, Zunker H, Heinlein A, Kühn MJ. (2024). *Towards Graph Neural Network Surrogates Leveraging Mechanistic Expert Knowledge for Pandemic Response*. arXiv. `https://arxiv.org/abs/2411.06500`
-- ODE-based models with Linear Chain Trick: Plötzke L, Wendler A, Schmieding R, Kühn MJ. (2024). *Revisiting the Linear Chain Trick in epidemiological models: Implications of underlying assumptions for numerical solutions*. Submitted for publication. `https://doi.org/10.48550/arXiv.2412.09140`
-- Behavior-based ODE models: Zunker H, Dönges P, Lenz P, Contreras S, Kühn MJ. (2025). *Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models*. Chaos, Solitons & Fractals. `https://doi.org/10.1016/j.chaos.2025.116782`
+- Ordinary differential equation-based (ODE) and Graph-ODE models: Zunker H, Schmieding R, Kerkmann D, Schengen A, Diexer S, et al. (2024). *Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios*. *PLOS Computational Biology* 20(12): e1012630. https://doi.org/10.1371/journal.pcbi.1012630
+- Integro-differential equation-based (IDE) models: Wendler A, Plötzke L, Tritzschak H, Kühn MJ. (2026). *A nonstandard numerical scheme for a novel SECIR integro differential equation-based model with nonexponentially distributed stay times*. *Applied Mathematics and Computation* 509: 129636. https://doi.org/10.1016/j.amc.2025.129636
+- Agent-based models (ABMs): Kerkmann D, Korf S, Nguyen K, Abele D, Schengen A, et al. (2025). *Agent-based modeling for realistic reproduction of human mobility and contact behavior to evaluate test and isolation strategies in epidemic infectious disease spread*. *Computers in Biology and Medicine* 193: 110269. https://doi.org/10.1016/j.compbiomed.2025.110269
+- Hybrid agent-metapopulation-based models: Bicker J, Schmieding R, Meyer-Hermann M, Kühn MJ. (2025). *Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing*. *Infectious Disease Modelling* 10(2): 571-590. https://doi.org/10.1016/j.idm.2024.12.015
+- Graph Neural Networks: Schmidt A, Zunker H, Heinlein A, Kühn MJ. (2025). *Graph Neural Network Surrogates to leverage Mechanistic Expert Knowledge towards Reliable and Immediate Pandemic Response*. Submitted for publication. https://doi.org/10.48550/arXiv.2411.06500
+- ODE-based models with Linear Chain Trick: Plötzke L, Wendler A, Schmieding R, Kühn MJ. (2024). *Revisiting the Linear Chain Trick in epidemiological models: Implications of underlying assumptions for numerical solutions*. Submitted for publication. https://doi.org/10.48550/arXiv.2412.09140
+- Behavior-based ODE models: Zunker H, Dönges P, Lenz P, Contreras S, Kühn MJ. (2025). *Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models*. Chaos, Solitons & Fractals. https://doi.org/10.1016/j.chaos.2025.116782
 
 
 **Getting started**
@@ -28,6 +28,12 @@ and, in particular, for
 The documentation for MEmilio can be found at 
 https://memilio.readthedocs.io/en/latest/index.html
 
+**Publication simulations**
+
+Simulations used for publications, along with their specific plotting and processing scripts, 
+are available in a separate repository:
+https://github.com/SciCompMod/memilio-simulations
+
 **Development**
 
 The coding guidelines and git workflow description can be found in the documentation at 

diff --git a/cpp/examples/smm.cpp b/cpp/examples/smm.cpp
@@ -19,6 +19,7 @@
 */
 
 #include "smm/simulation.h"
+#include "smm/model.h"
 #include "smm/parameters.h"
 #include "memilio/data/analyze_result.h"
 #include "memilio/epidemiology/adoption_rate.h"

diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
@@ -25,11 +25,13 @@ dl.class > dt:first-of-type {
 .rst-content dl .sig {
   width: -webkit-fill-available;
 }
+
 .rst-content .viewcode-link {
   display: inline-flex;
   float: inline-end;
   margin-right: 1.5em;
 }
+
 .rst-content .headerlink {
   position: absolute;
   right: 0.5em;
@@ -39,3 +41,48 @@ dl.class > dt:first-of-type {
 .wy-table-responsive table th {
   white-space: normal;
 }
+
+/* Team page styles */
+.developer-photo {
+  border-radius: 8px;
+  margin-right: 20px;
+  margin-bottom: 10px;
+  /* box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); */
+}
+
+/* Clear floats after each developer section */
+.section h3 {
+  clear: both;
+}
+
+/* Add some spacing between developer sections */
+.section>.section {
+  margin-bottom: 40px;
+  padding-bottom: 20px;
+  border-bottom: 1px solid #e1e4e5;
+}
+
+/* Style the links section */
+.section ul {
+  list-style-type: none;
+  padding-left: 0;
+}
+
+.section ul li {
+  margin-bottom: 5px;
+}
+
+.section ul li a {
+  color: #2980b9;
+  text-decoration: none;
+  font-weight: 500;
+}
+
+.section ul li a:hover {
+  text-decoration: underline;
+}
+
+.section p {
+  text-align: justify;
+  line-height: 1.6;
+}
diff --git a/docs/source/_static/funder/bmbf.jpg b/docs/source/_static/funder/bmbf.jpg
diff --git a/docs/source/_static/funder/bmdv.png b/docs/source/_static/funder/bmdv.png
diff --git a/docs/source/_static/funder/hdslee.png b/docs/source/_static/funder/hdslee.png
diff --git a/docs/source/_static/funder/helmholtz.jpg b/docs/source/_static/funder/helmholtz.jpg
diff --git a/docs/source/_static/funder/mfund.png b/docs/source/_static/funder/mfund.png
diff --git a/docs/source/_static/team/max_mustermann.jpg b/docs/source/_static/team/max_mustermann.jpg
diff --git a/docs/source/citation.rst b/docs/source/citation.rst
@@ -3,14 +3,15 @@ Citing MEmilio
 
 If you use MEmilio, please cite our work
 
-- Kühn, Martin Joachim et al. (2025). *MEmilio - a High Performance Modular Epidemics Simulation Software (2022)*. Available at `https://github.com/SciCompMod/memilio <https://github.com/SciCompMod/memilio>`_ and `https://elib.dlr.de/213614/ <https://elib.dlr.de/213614/>`_.
+- Bicker J, Kerkmann D, Korf S, Ploetzke L, Schmieding R, Wendler A, Zunker H et al. (2025). *MEmilio - a High Performance Modular Epidemics Simulation Software*. Available at `https://github.com/SciCompMod/memilio <https://github.com/SciCompMod/memilio>`_ and `https://elib.dlr.de/213614/ <https://elib.dlr.de/213614/>`_.
 
 and, in particular, for
 
 - **Ordinary differential equation-based (ODE) and Graph-ODE models**: Zunker H, Schmieding R, Kerkmann D, Schengen A, Diexer S, et al. (2024). *Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios*. *PLOS Computational Biology* 20(12): e1012630. `DOI:10.1371/journal.pcbi.1012630 <https://doi.org/10.1371/journal.pcbi.1012630>`_
-- **Integro-differential equation-based (IDE) models**: Wendler AC, Plötzke L, Tritzschak H, Kühn MJ. (2024). *A nonstandard numerical scheme for a novel SECIR integro differential equation-based model with nonexponentially distributed stay times*. Submitted for publication. `arXiv:2408.12228 <https://arxiv.org/abs/2408.12228>`_
+- **Integro-differential equation-based (IDE) models**: Wendler A, Plötzke L, Tritzschak H, Kühn MJ. (2026). *A nonstandard numerical scheme for a novel SECIR integro differential equation-based model with nonexponentially distributed stay times*. *Applied Mathematics and Computation* 509: 129636. `DOI:10.1016/j.amc.2025.129636 <https://doi.org/10.1016/j.amc.2025.129636>`_
 - **Agent-based models (ABMs)**: Kerkmann D, Korf S, Nguyen K, Abele D, Schengen A, et al. (2025). *Agent-based modeling for realistic reproduction of human mobility and contact behavior to evaluate test and isolation strategies in epidemic infectious disease spread*. *Computers in Biology and Medicine* 193: 110269. `DOI:10.1016/j.compbiomed.2025.110269 <https://doi.org/10.1016/j.compbiomed.2025.110269>`_
 - **Hybrid agent-metapopulation-based models**: Bicker J, Schmieding R, Meyer-Hermann M, Kühn MJ. (2025). *Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing*. *Infectious Disease Modelling* 10(2): 571-590. `DOI:10.1016/j.idm.2024.12.015 <https://doi.org/10.1016/j.idm.2024.12.015>`_
-- **Graph Neural Networks**: Schmidt A, Zunker H, Heinlein A, Kühn MJ. (2024).*Towards Graph Neural Network Surrogates Leveraging Mechanistic Expert Knowledge for Pandemic Response*. arXiv. `arXiv:2411.06500 <https://arxiv.org/abs/2411.06500>`_
-- **ODE-based models with Linear Chain Trick**: Plötzke L, Wendler A, Schmieding R, Kühn MJ. (2024). *Revisiting the Linear Chain Trick in epidemiological models: Implications of underlying assumptions for numerical solutions*. Submitted for publication. `DOI:10.48550/arXiv.2412.09140 <https://doi.org/10.48550/arXiv.2412.09140>`_
-- **Behavior-based ODE models**: Zunker H, Dönges P, Lenz P, Contreras S, Kühn MJ. (2025). *Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models*. arXiv. `arXiv:2502.14428 <https://arxiv.org/abs/2502.14428>`_
+- **Graph Neural Networks**: Schmidt A, Zunker H, Heinlein A, Kühn MJ. (2025). *Graph Neural Network Surrogates to leverage Mechanistic Expert Knowledge towards Reliable and Immediate Pandemic Response*. Submitted for publication. `arXiv:2411.06500 <https://arxiv.org/abs/2411.06500>`_
+- **ODE-based models with Linear Chain Trick**: Plötzke L, Wendler A, Schmieding R, Kühn MJ. (2024). *Revisiting the Linear Chain Trick in epidemiological models: Implications of underlying assumptions for numerical solutions*. Accepted for publication. `DOI:10.48550/arXiv.2412.09140 <https://doi.org/10.48550/arXiv.2412.09140>`_
+- **Behavior-based ODE models**: Zunker H, Dönges P, Lenz P, Contreras S, Kühn MJ. (2025). *Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models*. *Chaos, Solitons & Fractals* 199:116782. `DOI:10.1016/j.chaos.2025.116782 <https://doi.org/10.1016/j.chaos.2025.116782>`_
+
diff --git a/docs/source/cpp/aggregated_models.rst b/docs/source/cpp/aggregated_models.rst
@@ -6,8 +6,8 @@ There are different equation-based models implemented in MEmilio that consider a
 .. toctree::
     :maxdepth: 1
 
-    Ordinary differential equations <ode>
-    Linear Chain Trick <lct>
-    Generalized Linear Chain Trick <glct>
-    Stochastic-differential equations <sde>
-    Integro-differential equations <ide>
+    Ordinary differential equations (ODE) <ode>
+    Linear Chain Trick (LCT) <lct>
+    Generalized Linear Chain Trick (GLCT) <glct>
+    Integro-differential equations (IDE) <ide>    
+    Stochastic-differential equations (SDE) <sde>
diff --git a/docs/source/cpp/cpp_makros_preprocessing.rst b/docs/source/cpp/cpp_makros_preprocessing.rst
@@ -0,0 +1,104 @@
+Configuration macros
+-------------------
+
+MEmilio provides several compile-time configuration options through CMake that control which features and dependencies are available during compilation. These configurations are defined as preprocessor macros and can be used to conditionally compile code sections based on available libraries and enabled features.
+The following macros are automatically defined by CMake during the build process based on the availability of dependencies and build options:
+
+.. list-table::
+   :header-rows: 1
+   :widths: 30 70
+
+   * - Macro Name
+     - Description
+   * - :code:`MEMILIO_HAS_HDF5`
+     - Defined when HDF5 library is available. Enables HDF5 file I/O functionality for reading and writing results.
+   * - :code:`MEMILIO_HAS_JSONCPP`
+     - Defined when JsonCpp library is available. Enables JSON file I/O functionality for parameter import and configuration files.
+   * - :code:`MEMILIO_ENABLE_MPI`
+     - Defined when MPI (Message Passing Interface) support is enabled. Allows distributed computing and parallel simulations across multiple processes or compute nodes.
+   * - :code:`MEMILIO_ENABLE_OPENMP`
+     - Defined when OpenMP support is enabled. Enables shared-memory parallelization for multi-threaded execution within a single process.
+   * - :code:`MEMILIO_ENABLE_PROFILING`
+     - Defined when profiling support is enabled. Activates performance monitoring and timing instrumentation throughout the codebase.
+
+Usage in Code
+^^^^^^^^^^^^^^
+
+These macros are used with preprocessor conditionals to enable or disable specific functionality. You should use these macros to ensure that your code can compile and run correctly depending on the available libraries and features. 
+When using these macros, you should always consider fallbacks or alternative implementations when a feature is not available. This ensures that your code remains robust and can handle cases where optional dependencies are not present.
+Here are common usage patterns:
+
+**Conditional Compilation for Optional Dependencies**
+
+.. code-block:: cpp
+
+    #ifdef MEMILIO_HAS_JSONCPP
+    #include "memilio/io/epi_data.h"
+    #include "memilio/io/result_io.h"
+
+    // JSON-based parameter I/O functions
+    template <typename FP = double>
+    IOResult<void> read_divi_data(const std::string& path, 
+                                  const std::vector<int>& vregion, 
+                                  Date date,
+                                  std::vector<FP>& vnum_icu) {
+    }
+    #endif // MEMILIO_HAS_JSONCPP
+
+**HDF5-Specific Functionality**
+
+.. code-block:: cpp
+
+    #ifdef MEMILIO_HAS_HDF5
+    template <class Model>
+    IOResult<void> export_input_data_county_timeseries(
+        std::vector<Model> models, 
+        const std::string& results_dir,
+        /* ... other parameters ... */) {
+        // HDF5-based time series export
+    }
+    #else
+    template <class Model>
+    IOResult<void> export_input_data_county_timeseries(
+        std::vector<Model> models, 
+        const std::string& results_dir,
+        /* ... other parameters ... */) {
+        return failure(StatusCode::UnknownError, 
+                      "HDF5 not available");
+    }
+    #endif // MEMILIO_HAS_HDF5
+
+**Parallel Computing**
+
+.. code-block:: cpp
+
+    #ifdef MEMILIO_ENABLE_OPENMP
+    #include <omp.h>
+
+    void parallel_simulation() {
+        #pragma omp parallel for
+        for (int i = 0; i < num_regions; ++i) {
+            // Parallel execution of regional simulations
+        }
+    }
+    #endif // MEMILIO_ENABLE_OPENMP
+
+**Check Multiple Features Simultaneously**
+
+.. code-block:: cpp
+
+    // Check if both JSON and HDF5 are available
+    #if defined(MEMILIO_HAS_JSONCPP) && defined(MEMILIO_HAS_HDF5)
+    IOResult<void> read_and_export_data() {
+        // Implementation using both JSON input and HDF5 output
+    }
+    #elif defined(MEMILIO_HAS_JSONCPP)
+    IOResult<void> read_and_export_data() {
+        // JSON-only implementation
+    }
+    #else
+    IOResult<void> read_and_export_data() {
+        return failure(StatusCode::UnknownError, 
+                      "Neither JSON nor HDF5 available");
+    }
+    #endif