infection growth rate fitting

CovidAlertVaccinationModel/Manifest.toml

@@ -92,9 +92,9 @@ version = "1.16.0+6"
 
 [[ChainRulesCore]]
 deps = ["Compat", "LinearAlgebra", "SparseArrays"]
-git-tree-sha1 = "a66109c73612c63b10923ac446fddb0f0d21a593"
+git-tree-sha1 = "bd0cc939d94b8bd736dce5bbbe0d635db9f94af7"
 uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-version = "0.9.40"
+version = "0.9.41"
 
 [[CheapThreads]]
 deps = ["ArrayInterface", "IfElse", "Requires", "Static", "StrideArraysCore", "ThreadingUtilities", "VectorizationBase"]
@@ -120,6 +120,12 @@ git-tree-sha1 = "417b0ed7b8b838aa6ca0a87aadf1bb9eb111ce40"
 uuid = "5ae59095-9a9b-59fe-a467-6f913c188581"
 version = "0.12.8"
 
+[[CommonSubexpressions]]
+deps = ["MacroTools", "Test"]
+git-tree-sha1 = "7b8a93dba8af7e3b42fecabf646260105ac373f7"
+uuid = "bbf7d656-a473-5ed7-a52c-81e309532950"
+version = "0.3.0"
+
 [[Compat]]
 deps = ["Base64", "Dates", "DelimitedFiles", "Distributed", "InteractiveUtils", "LibGit2", "Libdl", "LinearAlgebra", "Markdown", "Mmap", "Pkg", "Printf", "REPL", "Random", "SHA", "Serialization", "SharedArrays", "Sockets", "SparseArrays", "Statistics", "Test", "UUIDs", "Unicode"]
 git-tree-sha1 = "ac4132ad78082518ec2037ae5770b6e796f7f956"
@@ -164,6 +170,12 @@ git-tree-sha1 = "3f71217b538d7aaee0b69ab47d9b7724ca8afa0d"
 uuid = "a8cc5b0e-0ffa-5ad4-8c14-923d3ee1735f"
 version = "4.0.4"
 
+[[CurveFit]]
+deps = ["LinearAlgebra", "Polynomials"]
+git-tree-sha1 = "eb0e0c7f3c49611223c7ed2d75ad98cfe6a9b18c"
+uuid = "5a033b19-8c74-5913-a970-47c3779ef25c"
+version = "0.3.5"
+
 [[DataAPI]]
 git-tree-sha1 = "dfb3b7e89e395be1e25c2ad6d7690dc29cc53b1d"
 uuid = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
@@ -171,9 +183,9 @@ version = "1.6.0"
 
 [[DataFrames]]
 deps = ["Compat", "DataAPI", "Future", "InvertedIndices", "IteratorInterfaceExtensions", "LinearAlgebra", "Markdown", "Missings", "PooledArrays", "PrettyTables", "Printf", "REPL", "Reexport", "SortingAlgorithms", "Statistics", "TableTraits", "Tables", "Unicode"]
-git-tree-sha1 = "78028b8c1c5147515e0a367e6bbe679fc86ff085"
+git-tree-sha1 = "6e5452d9cf401ed9048e1cde93815be53d951079"
 uuid = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-version = "1.0.1"
+version = "1.0.2"
 
 [[DataStructures]]
 deps = ["Compat", "InteractiveUtils", "OrderedCollections"]
@@ -211,6 +223,24 @@ git-tree-sha1 = "12e8b690de74848e9f41853817a94900a9e13bff"
 uuid = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4"
 version = "0.3.8"
 
+[[DiffResults]]
+deps = ["StaticArrays"]
+git-tree-sha1 = "c18e98cba888c6c25d1c3b048e4b3380ca956805"
+uuid = "163ba53b-c6d8-5494-b064-1a9d43ac40c5"
+version = "1.0.3"
+
+[[DiffRules]]
+deps = ["NaNMath", "Random", "SpecialFunctions"]
+git-tree-sha1 = "214c3fcac57755cfda163d91c58893a8723f93e9"
+uuid = "b552c78f-8df3-52c6-915a-8e097449b14b"
+version = "1.0.2"
+
+[[Distances]]
+deps = ["LinearAlgebra", "Statistics"]
+git-tree-sha1 = "366715149014943abd71aa647a07a43314158b2d"
+uuid = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
+version = "0.10.2"
+
 [[Distributed]]
 deps = ["Random", "Serialization", "Sockets"]
 uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b"
@@ -284,6 +314,18 @@ git-tree-sha1 = "31939159aeb8ffad1d4d8ee44d07f8558273120a"
 uuid = "1a297f60-69ca-5386-bcde-b61e274b549b"
 version = "0.11.7"
 
+[[FiniteDiff]]
+deps = ["ArrayInterface", "LinearAlgebra", "Requires", "SparseArrays", "StaticArrays"]
+git-tree-sha1 = "f6f80c8f934efd49a286bb5315360be66956dfc4"
+uuid = "6a86dc24-6348-571c-b903-95158fe2bd41"
+version = "2.8.0"
+
+[[FiniteDifferences]]
+deps = ["ChainRulesCore", "LinearAlgebra", "Printf", "Random", "Richardson", "StaticArrays"]
+git-tree-sha1 = "ae1ce4975c393bad81a55cb073e2af04bd151f85"
+uuid = "26cc04aa-876d-5657-8c51-4c34ba976000"
+version = "0.12.3"
+
 [[FixedPointNumbers]]
 deps = ["Statistics"]
 git-tree-sha1 = "335bfdceacc84c5cdf16aadc768aa5ddfc5383cc"
@@ -302,6 +344,12 @@ git-tree-sha1 = "8339d61043228fdd3eb658d86c926cb282ae72a8"
 uuid = "59287772-0a20-5a39-b81b-1366585eb4c0"
 version = "0.4.2"
 
+[[ForwardDiff]]
+deps = ["CommonSubexpressions", "DiffResults", "DiffRules", "LinearAlgebra", "NaNMath", "Printf", "Random", "SpecialFunctions", "StaticArrays"]
+git-tree-sha1 = "e2af66012e08966366a43251e1fd421522908be6"
+uuid = "f6369f11-7733-5829-9624-2563aa707210"
+version = "0.10.18"
+
 [[FreeType2_jll]]
 deps = ["Artifacts", "Bzip2_jll", "JLLWrappers", "Libdl", "Pkg", "Zlib_jll"]
 git-tree-sha1 = "cbd58c9deb1d304f5a245a0b7eb841a2560cfec6"
@@ -355,15 +403,15 @@ uuid = "7746bdde-850d-59dc-9ae8-88ece973131d"
 version = "2.59.0+4"
 
 [[Grisu]]
-git-tree-sha1 = "972f5abbfc7101df2ea122aa730f4861550aaf2f"
+git-tree-sha1 = "53bb909d1151e57e2484c3d1b53e19552b887fb2"
 uuid = "42e2da0e-8278-4e71-bc24-59509adca0fe"
-version = "1.0.1"
+version = "1.0.2"
 
 [[HTTP]]
 deps = ["Base64", "Dates", "IniFile", "MbedTLS", "NetworkOptions", "Sockets", "URIs"]
-git-tree-sha1 = "0e67ed09b3d89a28bb804ef5b886499f3a40a0cb"
+git-tree-sha1 = "b855bf8247d6e946c75bb30f593bfe7fe591058d"
 uuid = "cd3eb016-35fb-5094-929b-558a96fad6f3"
-version = "0.9.7"
+version = "0.9.8"
 
 [[Hwloc]]
 deps = ["Hwloc_jll"]
@@ -473,7 +521,9 @@ version = "0.6.2"
 
 [[KissABC]]
 deps = ["AbstractMCMC", "Distributions", "MonteCarloMeasurements", "Random"]
-git-tree-sha1 = "693d4bd4cbb9ad6515414e0935bbd646b15fc16a"
+git-tree-sha1 = "c6c85d271b03eb65021e3771eb620ed881078f83"
+repo-rev = "master"
+repo-url = "https://github.com/francescoalemanno/KissABC.jl.git"
 uuid = "9c9dad79-530a-4643-a18b-2704674d4108"
 version = "3.0.1"
 
@@ -605,6 +655,12 @@ version = "1.3.5"
 deps = ["Libdl"]
 uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 
+[[Loess]]
+deps = ["Distances", "LinearAlgebra", "Statistics"]
+git-tree-sha1 = "b5254a86cf65944c68ed938e575f5c81d5dfe4cb"
+uuid = "4345ca2d-374a-55d4-8d30-97f9976e7612"
+version = "0.5.3"
+
 [[LogExpFunctions]]
 deps = ["DocStringExtensions", "LinearAlgebra"]
 git-tree-sha1 = "ed26854d7c2c867d143f0e07c198fc9e8b721d10"
@@ -621,10 +677,16 @@ uuid = "e6f89c97-d47a-5376-807f-9c37f3926c36"
 version = "0.4.6"
 
 [[LoopVectorization]]
-deps = ["ArrayInterface", "CheapThreads", "DocStringExtensions", "IfElse", "LinearAlgebra", "OffsetArrays", "Requires", "SLEEFPirates", "Static", "ThreadingUtilities", "UnPack", "VectorizationBase"]
-git-tree-sha1 = "da82a865158e1d62e013fa72657fda7e92820a90"
+deps = ["ArrayInterface", "CheapThreads", "DocStringExtensions", "IfElse", "LinearAlgebra", "OffsetArrays", "Requires", "SLEEFPirates", "Static", "StrideArraysCore", "ThreadingUtilities", "UnPack", "VectorizationBase"]
+git-tree-sha1 = "50652d45832a4f907dbec3c57ac93af6f7d1f28c"
 uuid = "bdcacae8-1622-11e9-2a5c-532679323890"
-version = "0.12.12"
+version = "0.12.14"
+
+[[LsqFit]]
+deps = ["Distributions", "ForwardDiff", "LinearAlgebra", "NLSolversBase", "OptimBase", "Random", "StatsBase"]
+git-tree-sha1 = "0c33987800fbc37edf3a5fd94520e6b06783a63b"
+uuid = "2fda8390-95c7-5789-9bda-21331edee243"
+version = "0.12.0"
 
 [[MKL_jll]]
 deps = ["Artifacts", "IntelOpenMP_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "Pkg"]
@@ -680,13 +742,25 @@ version = "0.7.1"
 
 [[MonteCarloMeasurements]]
 deps = ["Distributed", "Distributions", "LinearAlgebra", "MacroTools", "Random", "RecipesBase", "Requires", "SLEEFPirates", "StaticArrays", "Statistics", "StatsBase", "Test"]
-git-tree-sha1 = "2529d92658cd24d197f7bc80a34a9109ad4f1970"
+git-tree-sha1 = "4852647c2dc2242e5b7e2907a96870a584a9488d"
 uuid = "0987c9cc-fe09-11e8-30f0-b96dd679fdca"
-version = "0.10.2"
+version = "0.10.3"
 
 [[MozillaCACerts_jll]]
 uuid = "14a3606d-f60d-562e-9121-12d972cd8159"
 
+[[MutableArithmetics]]
+deps = ["LinearAlgebra", "SparseArrays", "Test"]
+git-tree-sha1 = "3301e152b9a208745fad6cd4b068307a5d218a38"
+uuid = "d8a4904e-b15c-11e9-3269-09a3773c0cb0"
+version = "0.2.18"
+
+[[NLSolversBase]]
+deps = ["DiffResults", "Distributed", "FiniteDiff", "ForwardDiff"]
+git-tree-sha1 = "50608f411a1e178e0129eab4110bd56efd08816f"
+uuid = "d41bc354-129a-5804-8e4c-c37616107c6c"
+version = "7.8.0"
+
 [[NaNMath]]
 git-tree-sha1 = "bfe47e760d60b82b66b61d2d44128b62e3a369fb"
 uuid = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
@@ -720,9 +794,9 @@ version = "1.3.4+2"
 
 [[OnlineStats]]
 deps = ["AbstractTrees", "Dates", "LinearAlgebra", "OnlineStatsBase", "OrderedCollections", "Random", "RecipesBase", "Statistics", "StatsBase", "SweepOperator"]
-git-tree-sha1 = "a3d0e72ffde4f596cc148c4c6555e310dcd5b2ba"
+git-tree-sha1 = "042eb860cc994aa73b517f326922b03827bbc159"
 uuid = "a15396b6-48d5-5d58-9928-6d29437db91e"
-version = "1.5.8"
+version = "1.5.9"
 
 [[OnlineStatsBase]]
 deps = ["AbstractTrees", "Dates", "LinearAlgebra", "OrderedCollections", "Statistics", "StatsBase"]
@@ -742,6 +816,12 @@ git-tree-sha1 = "b9b8b8ed236998f91143938a760c2112dceeb2b4"
 uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
 version = "0.5.4+0"
 
+[[OptimBase]]
+deps = ["NLSolversBase", "Printf", "Reexport"]
+git-tree-sha1 = "4c26a757fbb5b1893b7df19a44e21762d8f8e470"
+uuid = "87e2bd06-a317-5318-96d9-3ecbac512eee"
+version = "2.0.1"
+
 [[Opus_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
 git-tree-sha1 = "f9d57f4126c39565e05a2b0264df99f497fc6f37"
@@ -810,6 +890,12 @@ git-tree-sha1 = "eced322de627fa8469c55f24899fdd4cce7d978c"
 uuid = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 version = "1.13.2"
 
+[[Polynomials]]
+deps = ["Intervals", "LinearAlgebra", "MutableArithmetics", "RecipesBase"]
+git-tree-sha1 = "3606b3e972f7a58b62432c95aa2bdab3f3d97831"
+uuid = "f27b6e38-b328-58d1-80ce-0feddd5e7a45"
+version = "2.0.10"
+
 [[PooledArrays]]
 deps = ["DataAPI", "Future"]
 git-tree-sha1 = "cde4ce9d6f33219465b55162811d8de8139c0414"
@@ -840,9 +926,9 @@ version = "0.1.4"
 
 [[ProgressMeter]]
 deps = ["Distributed", "Printf"]
-git-tree-sha1 = "6e9c89cba09f6ef134b00e10625590746ba1e036"
+git-tree-sha1 = "d85d8f0339a9937afac93e152c76f4745b386202"
 uuid = "92933f4c-e287-5a05-a399-4b506db050ca"
-version = "1.5.0"
+version = "1.6.0"
 
 [[PyCall]]
 deps = ["Conda", "Dates", "Libdl", "LinearAlgebra", "MacroTools", "Serialization", "VersionParsing"]
@@ -893,9 +979,10 @@ uuid = "01d81517-befc-4cb6-b9ec-a95719d0359c"
 version = "0.3.2"
 
 [[Reexport]]
-git-tree-sha1 = "57d8440b0c7d98fc4f889e478e80f268d534c9d5"
+deps = ["Pkg"]
+git-tree-sha1 = "7b1d07f411bc8ddb7977ec7f377b97b158514fe0"
 uuid = "189a3867-3050-52da-a836-e630ba90ab69"
-version = "1.0.0"
+version = "0.2.0"
 
 [[Referenceables]]
 deps = ["Adapt"]
@@ -909,6 +996,12 @@ git-tree-sha1 = "4036a3bd08ac7e968e27c203d45f5fff15020621"
 uuid = "ae029012-a4dd-5104-9daa-d747884805df"
 version = "1.1.3"
 
+[[Richardson]]
+deps = ["LinearAlgebra"]
+git-tree-sha1 = "e03ca566bec93f8a3aeb059c8ef102f268a38949"
+uuid = "708f8203-808e-40c0-ba2d-98a6953ed40d"
+version = "1.4.0"
+
 [[Rmath]]
 deps = ["Random", "Rmath_jll"]
 git-tree-sha1 = "bf3188feca147ce108c76ad82c2792c57abe7b1f"
@@ -957,9 +1050,9 @@ uuid = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
 
 [[Showoff]]
 deps = ["Dates", "Grisu"]
-git-tree-sha1 = "236dd0ddad6e3764cce8d8b09c0bbba6df2e194f"
+git-tree-sha1 = "91eddf657aca81df9ae6ceb20b959ae5653ad1de"
 uuid = "992d4aef-0814-514b-bc4d-f2e9a6c4116f"
-version = "1.0.2"
+version = "1.0.3"
 
 [[SimpleTraits]]
 deps = ["InteractiveUtils", "MacroTools"]
@@ -971,10 +1064,10 @@ version = "0.9.3"
 uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
 
 [[SortingAlgorithms]]
-deps = ["DataStructures", "Random", "Test"]
-git-tree-sha1 = "03f5898c9959f8115e30bc7226ada7d0df554ddd"
+deps = ["DataStructures"]
+git-tree-sha1 = "2ec1962eba973f383239da22e75218565c390a96"
 uuid = "a2af1166-a08f-5f64-846c-94a0d3cef48c"
-version = "0.3.1"
+version = "1.0.0"
 
 [[SparseArrays]]
 deps = ["LinearAlgebra", "Random"]
@@ -1008,11 +1101,16 @@ version = "1.1.2"
 deps = ["LinearAlgebra", "SparseArrays"]
 uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
+[[StatsAPI]]
+git-tree-sha1 = "1958272568dc176a1d881acb797beb909c785510"
+uuid = "82ae8749-77ed-4fe6-ae5f-f523153014b0"
+version = "1.0.0"
+
 [[StatsBase]]
-deps = ["DataAPI", "DataStructures", "LinearAlgebra", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics"]
-git-tree-sha1 = "4d8ca45223d7a28839e775d73a6f6b6b2ac64fd1"
+deps = ["DataAPI", "DataStructures", "LinearAlgebra", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics", "StatsAPI"]
+git-tree-sha1 = "2f6792d523d7448bbe2fec99eca9218f06cc746d"
 uuid = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
-version = "0.33.6"
+version = "0.33.8"
 
 [[StatsFuns]]
 deps = ["LogExpFunctions", "Rmath", "SpecialFunctions"]
@@ -1092,9 +1190,9 @@ version = "0.1.7"
 
 [[TimeZones]]
 deps = ["Dates", "EzXML", "Mocking", "Pkg", "Printf", "RecipesBase", "Serialization", "Unicode"]
-git-tree-sha1 = "4ba8a9579a243400db412b50300cd61d7447e583"
+git-tree-sha1 = "3f6f0be07f33e33bd986a58b4cf2d6c9fd2b7f18"
 uuid = "f269a46b-ccf7-5d73-abea-4c690281aa53"
-version = "1.5.3"
+version = "1.5.4"
 
 [[Transducers]]
 deps = ["Adapt", "ArgCheck", "BangBang", "Baselet", "CompositionsBase", "DefineSingletons", "Distributed", "InitialValues", "Logging", "Markdown", "MicroCollections", "Requires", "Setfield", "SplittablesBase", "Tables"]
@@ -1103,9 +1201,9 @@ uuid = "28d57a85-8fef-5791-bfe6-a80928e7c999"
 version = "0.4.64"
 
 [[URIs]]
-git-tree-sha1 = "7855809b88d7b16e9b029afd17880930626f54a2"
+git-tree-sha1 = "97bbe755a53fe859669cd907f2d96aee8d2c1355"
 uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
-version = "1.2.0"
+version = "1.3.0"
 
 [[UUIDs]]
 deps = ["Random", "SHA"]
@@ -1121,9 +1219,9 @@ uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
 
 [[VectorizationBase]]
 deps = ["ArrayInterface", "Hwloc", "IfElse", "Libdl", "LinearAlgebra", "Static"]
-git-tree-sha1 = "5d66756d2d5c538e9ab0c39efcb4512e3a8c3361"
+git-tree-sha1 = "293aa2c5cbf201e6b98810cb36d9eeafdafdafd1"
 uuid = "3d5dd08c-fd9d-11e8-17fa-ed2836048c2f"
-version = "0.19.31"
+version = "0.19.34"
 
 [[VersionParsing]]
 git-tree-sha1 = "80229be1f670524750d905f8fc8148e5a8c4537f"

CovidAlertVaccinationModel/Project.toml

@@ -6,13 +6,17 @@ version = "0.1.0"
 [deps]
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+CurveFit = "5a033b19-8c74-5913-a970-47c3779ef25c"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
 Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
+FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
 ImportAll = "c65182e5-40f4-518f-8165-175b85689199"
+Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 Intervals = "d8418881-c3e1-53bb-8760-2df7ec849ed5"
 KernelDensity = "5ab0869b-81aa-558d-bb23-cbf5423bbe9b"
 KissABC = "9c9dad79-530a-4643-a18b-2704674d4108"
@@ -20,7 +24,9 @@ LaTeXStrings = "b964fa9f-0449-5b57-a5c2-d3ea65f4040f"
 LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+Loess = "4345ca2d-374a-55d4-8d30-97f9976e7612"
 LoopVectorization = "bdcacae8-1622-11e9-2a5c-532679323890"
+LsqFit = "2fda8390-95c7-5789-9bda-21331edee243"
 NamedTupleTools = "d9ec5142-1e00-5aa0-9d6a-321866360f50"
 NetworkLayout = "46757867-2c16-5918-afeb-47bfcb05e46a"
 OnlineStats = "a15396b6-48d5-5d58-9928-6d29437db91e"

CovidAlertVaccinationModel/abm_fit_parameters.jl

 using CovidAlertVaccinationModel
 using OnlineStats
 using Plots
-const samples = 1
 const parameters = (
-    sim_length = 50,
+    sim_length = 30,
     num_households = 5000,
-    I_0_fraction = 0.002,
-    base_transmission_probability = 0.0015,
+    I_0_fraction = 0.005,
+    base_transmission_probability = 0.001,
     recovery_rate = 1/7,
     immunization_loss_prob = 0.0055, #mean time of 6 months
-    π_base = -0.2,
-    κ = 0.001,
-    ω = 0.0000,
-    ρ = [0.0,0.0,0.0],
+    π_base = -4.0,
     η = 0.0,
+    κ = 1.0,
+    ω = 0.001,
+    ρ = [0.0,0.0,0.0],
     ω_en = 0.00,
     ρ_en =  [0.0,0.0,0.0],
     γ = 0.0,
-    β = 100.0,
-    notification_parameter = 0.000,
+    β = 5.0,
+    notification_parameter = 0.001,
     vaccinator_prob = 0.2,
     app_user_fraction = 0.4,
     notification_threshold = 2,
-    infection_introduction_delay = 50
-    immunizing = true,
+    immunizing = false,
+    immunization_delay = 14,
+    immunization_begin_delay = 0,
+    infection_introduction_delay = 1,
 )
-function solve_and_plot_parameters()
-    out = mean_solve(samples, parameters ,DebugRecorder)
-    p = plot_model(nothing,[nothing],[out])
-    savefig(p,"timeseries.pdf")
-end
 
-solve_and_plot_parameters()
\ No newline at end of file
+seasonal_transmission_dist = CovidAlertVaccinationModel.fit_epi_parameters(parameters,0.073) ##seasonal
+# outbreak_transmission_dist = CovidAlertVaccinationModel.fit_epi_parameters(parameters,0.241) ##outbreak
\ No newline at end of file

CovidAlertVaccinationModel/abm_timeseries.jl

 using CovidAlertVaccinationModel
 using OnlineStats
 using Plots
-const samples = 5
+const samples = 2
 const parameters = (
     sim_length = 600,
     num_households = 5000,

CovidAlertVaccinationModel/src/ABM/model_setup.jl

@@ -32,7 +32,22 @@ function get_u_0(nodes,I_0_fraction,vaccinator_prob)
     return status,is_vaccinator
 end
 
-struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
+function app_users(demographics,app_usage_prob)
+    ymo_usage = [
+        0.979,
+        0.921,
+        0.604,  
+    ]
+    is_app_user = Vector{Bool}(undef,length(demographics))
+    @inbounds for i in eachindex(demographics)
+        demo = demographics[i]
+        is_app_user[i] = rand(RNG) < app_usage_prob*ymo_usage[Int(demo)]
+    end
+    return is_app_user
+end
+
+
+mutable struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
     sim_length::Int
     nodes::Int
     params::T
@@ -50,7 +65,8 @@ struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
     app_user_list::Vector{Int}
     app_user_index::Vector{Int}
     status_totals::Vector{Int}
-    status_totals_next::Vector{Int}
+    daily_vaccinators::Int
+    daily_infected::Int
     ws_matrix_tuple::WSMixingDist
     rest_matrix_tuple::RestMixingDist
     immunization_countdown::Vector{Int}
@@ -63,8 +79,8 @@ struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
         ws_matrix_tuple = map_symmetrize(workschool_mixing)
         rest_matrix_tuple = map_symmetrize(rest_mixing)
 
+        is_app_user = app_users(demographics,params.app_user_fraction)
         app_user_list = zeros(nodes)
-        is_app_user = rand(RNG,nodes) .< params.app_user_fraction
         app_user_index = findall(==(true),is_app_user)
         app_user_list[is_app_user] .= collect(1:length(app_user_index))
         
@@ -95,7 +111,8 @@ struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
             app_user_list,
             app_user_index,
             status_totals,
-            copy(status_totals),
+            0,
+            0,
             ws_matrix_tuple,
             rest_matrix_tuple,
             immunization_countdown

CovidAlertVaccinationModel/src/ABM/output.jl

@@ -18,6 +18,7 @@ DebugRecorder should store everything we might want to know about the model outp
 """
 struct DebugRecorder{ElType,ArrType1<:AbstractArray{ElType},ArrType2<:AbstractArray{ElType}} <: AbstractRecorder{ElType}
     recorded_status_totals::ArrType1
+    daily_cases::ArrType2
     total_vaccinators::ArrType2
     mean_time_since_last_notification::ArrType2
 end
@@ -29,8 +30,10 @@ function DebugRecorder(sim_length)
     state_totals = @LArray Array{Int}(undef,4,sim_length) (S = (1,:),I = (2,:),R = (3,:), V = (4,:))
     total_vaccinators = Vector{Int}(undef,sim_length)
     mean_time_since_last_notification = Vector{Int}(undef,sim_length)
+    daily_cases= Vector{Int}(undef,sim_length)
     return DebugRecorder(
         state_totals,
+        daily_cases,
         total_vaccinators,
         mean_time_since_last_notification,
     )
@@ -46,16 +49,18 @@ function DebugRecorder(val::T, sim_length) where T
     total_vaccinators = [copy(val) for j in 1:sim_length]
 
     mean_time_since_last_notification = [copy(val) for j in 1:sim_length]
-
+    daily_cases =  [copy(val) for j in 1:sim_length]
     return DebugRecorder(
         state_totals,
+        daily_cases,
         total_vaccinators,
         mean_time_since_last_notification
     )
 end
 
 function record!(t,modelsol, recorder::DebugRecorder)
-    recorder.total_vaccinators[t] = count(==(true),modelsol.u_vac)
+    recorder.total_vaccinators[t] = modelsol.daily_vaccinators
+    recorder.daily_cases[t] = modelsol.daily_infected
     recorder.recorded_status_totals[:,t] .= modelsol.status_totals
     alerts = filter(>(0),modelsol.time_of_last_alert)
     if !isempty(alerts)
@@ -93,7 +98,7 @@ end
 using Printf
 const ts_colors = cgrad(:PuBu_9)
 function plot_model(varname,univariate_series, output_list::Vector{T},infection_begin,vac_begin) where T<:DebugRecorder
-    plts = [plot(),plot(),plot(),plot(),plot(),plot()]
+    plts = [plot() for i=1:7]
     for (i,(p,data)) in enumerate(zip(univariate_series, output_list))
         # display(p[varname])
         if !isnothing(varname) 
@@ -117,6 +122,7 @@ function plot_model(varname,univariate_series, output_list::Vector{T},infection_
                 title = "Infected over time",
                 legend=false,
         )
+        
         plot!(plts[3], mean.(data.recorded_status_totals.R); ribbon = std.(data.recorded_status_totals.R),
                 label = labelname, line_z = i, color=:blues,
                 ylabel = "no. of people",
@@ -145,10 +151,21 @@ function plot_model(varname,univariate_series, output_list::Vector{T},infection_
                 title = "Mean time since last notification",
                 legend=false
         )
+
+
+        # ic,exp_growth_rate = exp_growth_rate_estimation(mean.(data.daily_cases[infection_begin,:]))
+
+        plot!(plts[7], mean.(data.daily_cases); ribbon = std.(data.daily_cases),
+                label = labelname, line_z = i, color=:blues,
+                ylabel = "Days",
+                colorbar = false,
+                title = "Daily (incident) cases",
+                legend= false
+        )
     end
     for p in plts
         vline!(p,[infection_begin]; label = "infection begin", line =:dot)
         vline!(p,[vac_begin]; label = "vaccination begin",line = :dot)
     end
-    return plot(plts...;layout = (6,1),size=(800,2500),leftmargin = 8Plots.mm)
+    return plot(plts...;layout = (7,1),size=(800,2900),leftmargin = 8Plots.mm)
 end

CovidAlertVaccinationModel/src/ABM/parameter_optimization.jl

+using KissABC
+using CurveFit
+using Loess
+
+
+@views function exp_growth_rate_estimation(incident_cases)
+
+
+    diff(l) = [l[i] - l[i-1] for i=2:length(l)]
+    l = length(incident_cases)
+    loess_interp = loess(1:l,incident_cases)
+    interp_incident_cases = Loess.predict(loess_interp, collect(1.0:l))
+    second_deriative =diff(diff(interp_incident_cases))
+    inflection_pt = any(second_deriative.<=-1) ? findfirst(<=(-1),second_deriative) : l  #completely heuristic
+    ic,exp_growth_rate = exp_fit(1:inflection_pt, incident_cases[1:inflection_pt]) #fit y = a exp(b x), b is exp growth rate
+    return ic,exp_growth_rate
+end
+
+
+function vaccination_data()
+    
+
+end
+
+function fit_epi_parameters(p_tuple, target_growth_rate)
+    samples = 1
+    priors = Factored(Uniform(0.0001,0.005))    
+    function cost(p)
+        new_params = merge(p_tuple, (base_transmission_probability = p[1],))
+        out = mean_solve(samples, new_params ,DebugRecorder)
+        incident_cases = mean.(out.daily_cases)
+        _,exp_growth_rate = exp_growth_rate_estimation(incident_cases)
+        return (target_growth_rate - exp_growth_rate)^2
+    end
+    out = ABCDE(priors,cost,0.01; verbose=true, nparticles=100,generations=20,  parallel = true) #this one has better NaN handling
+    return out
+end
+
+
+function fit_behavioural_parameters(p_tuple, target_growth_rate)
+    samples = 1
+    priors = Factored(Uniform(0.0001,0.005))    
+    function cost(p)
+        new_params = merge(p_tuple, (base_transmission_probability = p[1],))
+        out = mean_solve(samples, new_params ,DebugRecorder)
+        incident_cases = mean.(out.daily_cases)
+        _,exp_growth_rate = exp_growth_rate_estimation(incident_cases)
+        return (target_growth_rate - exp_growth_rate)^2
+    end
+    out = ABCDE(priors,cost,0.01; verbose=true, nparticles=100,generations=20,  parallel = true) #this one has better NaN handling
+    return out
+end
\ No newline at end of file

CovidAlertVaccinationModel/src/ABM/solve.jl

@@ -42,6 +42,7 @@ end
 Base.@propagate_inbounds @views function update_infection_state!(t,modelsol)
     @unpack base_transmission_probability,immunization_loss_prob,recovery_rate,immunizing,immunization_begin_delay = modelsol.params
     @unpack u_inf,u_vac,u_next_inf,u_next_vac,demographics,inf_network,status_totals, immunization_countdown = modelsol
+    daily_cases = 0
     
     function agent_transition!(node, from::AgentStatus,to::AgentStatus) 
         immunization_countdown[node] = -1 
@@ -49,7 +50,6 @@ Base.@propagate_inbounds @views function update_infection_state!(t,modelsol)
         status_totals[Int(to)] += 1
         u_next_inf[node] = to
     end
-
     u_next_inf .= u_inf
     for i in 1:modelsol.nodes
         agent_status = u_inf[i]
@@ -63,6 +63,7 @@ Base.@propagate_inbounds @views function update_infection_state!(t,modelsol)
                     for j in neighbors(mixing_graph.g,i)    
                         if u_inf[j] == Infected && u_next_inf[i] != Infected 
                             if rand(RNG) < contact_weight(base_transmission_probability,get_weight(mixing_graph,GraphEdge(i,j)))
+                                daily_cases+=1
                                 agent_transition!(i, Susceptible,Infected)
                             end
                         end
@@ -87,13 +88,12 @@ Base.@propagate_inbounds @views function update_infection_state!(t,modelsol)
             immunization_countdown[i] -= 1
         end
     end
-    # display(immunization_countdown)
+    modelsol.daily_infected = daily_cases
 end
 Base.@propagate_inbounds @views function update_vaccination_opinion_state!(t,modelsol,total_infections)
     @unpack π_base, η,γ, κ, ω, ρ, ω_en,ρ_en,γ,β = modelsol.params
     @unpack demographics,time_of_last_alert, nodes, soc_network,u_vac,u_next_vac,app_user,app_user_list = modelsol
     app_user_pointer = 0
-
     for i in 1:nodes
         vac_payoff = 0
         soc_nbrs_vac = @MArray [0,0,0]
@@ -131,6 +131,8 @@ Base.@propagate_inbounds @views function update_vaccination_opinion_state!(t,mod
             end
         end
     end
+
+    modelsol.daily_vaccinators = count(==(true),u_vac)
 end
 
 
@@ -161,11 +163,11 @@ end
 function solve!(modelsol,recordings...)
 
     for t in 1:modelsol.sim_length
+        agents_step!(t,modelsol) 
         #advance agent states based on the new network
         for recording in recordings
             record!(t,modelsol,recording)
         end
-        agents_step!(t,modelsol) 
     end
 end
 

CovidAlertVaccinationModel/src/CovidAlertVaccinationModel.jl

@@ -51,6 +51,7 @@ include("ABM/mixing_distributions.jl")
 include("ABM/mixing_graphs.jl")
 include("ABM/agents.jl")
 include("ABM/model_setup.jl")
+include("ABM/parameter_optimization.jl")
 include("ABM/output.jl")
 include("ABM/solve.jl")
 include("ABM/abm.jl")